GUCY1A3 Antibody, HRP conjugated

What is GUCY1A3 and why is it important in cardiovascular research?

GUCY1A3 encodes the α1-subunit of soluble guanylyl cyclase (sGC), a heterodimeric enzyme consisting of α1 and β1 subunits that functions as the primary receptor for nitric oxide (NO). This enzyme catalyzes the conversion of GTP to cGMP, a critical second messenger that regulates smooth muscle contractility, platelet reactivity, and neurotransmission .

The importance of GUCY1A3 in cardiovascular research stems from genome-wide association studies identifying it as a coronary artery disease (CAD) risk locus. Specifically, the rs7692387 variant in GUCY1A3 is significantly associated with increased CAD risk, with the G allele carriers showing lower GUCY1A3 expression levels . This genetic evidence, coupled with the critical role of the NO-sGC-cGMP pathway in vascular homeostasis, makes GUCY1A3 a central focus in cardiovascular disease research.

In mouse models, higher GUCY1A3 expression levels correlate with reduced atherosclerosis development, further supporting its protective role in vascular health . Additionally, the enzyme contains a heme moiety that mediates NO activation and can also bind carbon monoxide, which weakly stimulates the enzyme .

What are the key applications of GUCY1A3 antibodies in research laboratories?

GUCY1A3 antibodies, particularly HRP-conjugated versions, serve numerous research applications:

• Western blotting: Detecting and quantifying GUCY1A3 protein expression in tissue and cell lysates, with recommended dilutions typically ranging from 1:100-1:1000 .

• Immunohistochemistry (IHC): Visualizing the tissue and cellular distribution of GUCY1A3, particularly useful for examining expression patterns in vascular tissues and disease models at dilutions of 1:100-500 .

• Protein localization studies: Determining subcellular localization and expression changes during disease progression or in response to treatments.

• Genotype-phenotype correlation studies: Examining protein expression differences between individuals with different GUCY1A3 genetic variants, particularly the rs7692387 polymorphism .

• Mechanistic investigations: Studying the relationship between GUCY1A3 expression and functional outcomes such as platelet aggregation or vascular smooth muscle cell migration .

HRP-conjugated antibodies offer particular advantages for detection systems that rely on enzymatic conversion of substrates to produce visible signals, eliminating the need for secondary antibody incubation steps.

How does GUCY1A3 function in the NO-sGC-cGMP signaling pathway?

GUCY1A3 is an essential component of the NO-sGC-cGMP signaling cascade:

• Receptor formation: The α1-subunit (encoded by GUCY1A3) combines with the β1-subunit to form the functional sGC heterodimer, which acts as the primary receptor for nitric oxide .

• Signal transduction: When NO binds to the heme group in sGC, it triggers a conformational change that dramatically increases the enzyme's catalytic activity (up to 200-fold) .

• Second messenger generation: Activated sGC converts GTP to cGMP, which serves as a second messenger that activates protein kinases, ion channels, and phosphodiesterases.

• Physiological effects: The resulting cGMP signaling mediates multiple cardiovascular protective functions:

  • Vascular smooth muscle relaxation

  • Inhibition of platelet aggregation

  • Reduction of smooth muscle cell proliferation

  • Modulation of inflammatory responses

• Pharmacological modulation: The pathway can be enhanced through NO donors, sGC stimulators/activators, or phosphodiesterase inhibitors like sildenafil .

Reduced GUCY1A3 expression, as seen with the rs7692387 risk allele, leads to decreased sGC activity and attenuated NO signaling, potentially contributing to increased cardiovascular disease risk .

What are the optimal protocols for Western blotting using GUCY1A3 HRP-conjugated antibodies?

For optimal Western blotting results with GUCY1A3 HRP-conjugated antibodies, follow these methodological guidelines:

• Sample preparation:

  • Extract proteins using RIPA buffer supplemented with protease inhibitors

  • For platelets or vascular tissues, include phosphatase inhibitors to preserve post-translational modifications

  • Quantify protein concentration using BCA or Bradford assays for consistent loading

• Gel electrophoresis:

  • Use 8-10% SDS-PAGE gels for optimal resolution of GUCY1A3 (77-82 kDa)

  • Load 25-35 μg total protein per lane for most tissue samples

  • Include positive controls (e.g., 293 cells transfected with GUCY1A3 gene)

• Transfer and blocking:

  • Transfer to PVDF membranes (preferred over nitrocellulose for better protein retention)

  • Block with 5% non-fat dry milk or BSA in TBST for 1 hour at room temperature

  • For phosphorylation studies, use 5% BSA rather than milk

• Antibody incubation:

  • Dilute HRP-conjugated GUCY1A3 antibody at 1:100-1:1000 in blocking buffer

  • Incubate overnight at 4°C for optimal signal-to-noise ratio

  • Wash extensively (4× 5 minutes) with TBST after antibody incubation

• Detection and analysis:

  • Use enhanced chemiluminescence (ECL) substrate appropriate for expected expression level

  • Capture images using digital imaging systems for better quantification

  • Normalize to loading controls (β-actin, GAPDH) for accurate comparison between samples

Troubleshooting tip: If non-specific bands appear, increase washing stringency and optimize antibody dilution. For weak signals, extend exposure time or use signal enhancers.

How should immunohistochemistry protocols be optimized for GUCY1A3 detection in cardiovascular tissues?

Immunohistochemical detection of GUCY1A3 in cardiovascular tissues requires specific protocol optimization:

• Tissue preparation and fixation:

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

  • Paraffin embedding following standard protocols

  • Section tissues at 4-6 μm thickness for optimal antibody penetration

  • Mount sections on positively charged slides to prevent tissue loss

• Antigen retrieval methods:

  • Heat-induced epitope retrieval using citrate buffer (pH 6.0) provides optimal results

  • Pressure cooking for 15-20 minutes generally achieves better retrieval than microwave methods

  • Allow slides to cool slowly in retrieval solution for 20 minutes before proceeding

• Blocking and antibody application:

  • Block endogenous peroxidase with 3% H₂O₂ for 10 minutes

  • Block non-specific binding with 5-10% normal serum

  • Apply HRP-conjugated GUCY1A3 antibody at 1:100-1:500 dilution

  • Incubate in humidified chamber overnight at 4°C

• Development and counterstaining:

  • Develop with DAB or AEC substrate (3-5 minutes, monitoring microscopically)

  • Counterstain with hematoxylin for nuclear visualization (30-60 seconds)

  • Mount with appropriate medium based on the substrate used

• Controls and validation:

  • Include negative controls (primary antibody omitted)

  • Use tissues with known GUCY1A3 expression as positive controls

  • Consider vascular smooth muscle cells and platelets as high-expression positive controls

The formalin-fixed, paraffin-embedded tissue samples shown in published data demonstrate that proper optimization allows detection of GUCY1A3 in various tissues including breast carcinoma and hepatocarcinoma .

What methodological approaches can detect differences in GUCY1A3 expression between genotype groups?

To accurately detect expression differences between GUCY1A3 genotype groups (particularly rs7692387 variants), implement these methodological approaches:

• Genotype determination:

  • Use PCR-based genotyping or next-generation sequencing to identify rs7692387 variants

  • Group samples as G/G (risk allele homozygotes), G/A (heterozygotes), or A/A (non-risk allele homozygotes)

  • Ensure adequate sample sizes in each genotype group for statistical power

• Protein quantification techniques:

  • Western blotting with HRP-conjugated antibodies for semi-quantitative analysis

  • Calibrate using recombinant protein standards for absolute quantification

  • Perform densitometric analysis with normalization to loading controls

  • Consider multiplexed approaches to reduce inter-blot variability

• Tissue-specific considerations:

  • Vascular tissue: Separate media (smooth muscle) from endothelium for cell-specific analysis

  • Platelets: Standardize isolation procedures to minimize activation

  • Brain tissue: Regional analysis may be necessary due to expression heterogeneity

• Functional correlation studies:

  • Measure sGC activity using cGMP assays in samples from different genotype groups

  • Assess NO-induced platelet inhibition as a functional readout

  • Evaluate vascular smooth muscle cell migration in response to pathway stimulation

• Data analysis approaches:

  • Use ANOVA with post-hoc tests for multi-group comparisons

  • Consider covariates that might influence expression (age, sex, medications)

  • Calculate expression ratios between genotype groups for consistent reporting

Research has demonstrated that individuals homozygous for the rs7692387 risk (G) allele show significantly lower GUCY1A3 mRNA and protein levels compared to non-risk allele carriers, with differences maintained at the functional level .

How can GUCY1A3 antibodies help investigate pharmacogenetic interactions with aspirin therapy?

GUCY1A3 antibodies provide valuable tools for investigating the pharmacogenetic interaction between GUCY1A3 variants and aspirin therapy:

• Expression monitoring in clinical samples:

  • Quantify GUCY1A3 protein levels in platelets from patients with different rs7692387 genotypes

  • Compare baseline levels and changes after aspirin therapy

  • Correlate protein expression with clinical outcomes in aspirin-treated patients

• Functional assessment of platelet activity:

  • Measure GUCY1A3 protein levels alongside platelet function tests

  • Assess aspirin-induced changes in NO sensitivity between genotype groups

  • Correlate protein expression with platelet aggregation responses

• Mechanistic investigations:

  • Study protein-protein interactions between GUCY1A3 and cyclooxygenase pathways

  • Evaluate post-translational modifications of GUCY1A3 in response to aspirin

  • Assess downstream signaling pathway activation using phospho-specific antibodies

• Translational research applications:

  • Develop immunoassays to identify patients likely to benefit from aspirin therapy

  • Create point-of-care tests to guide personalized aspirin dosing

  • Monitor therapy response in patients with different genotypes

• Clinical trial stratification:

  • Use antibody-based assays to prospectively stratify patients in clinical trials

  • Correlate baseline GUCY1A3 levels with treatment outcomes

  • Develop prediction models incorporating protein expression and genotype

Research has shown that rs7692387 genotype significantly influences aspirin therapy outcomes in primary prevention of cardiovascular disease. In randomized trials, aspirin reduced cardiovascular events in homozygous G allele carriers (OR 0.79) but increased events in heterozygotes (OR 1.39), demonstrating a significant genotype-treatment interaction (P-interaction = 0.01) .

What approaches can reveal the relationship between GUCY1A3 expression and vascular smooth muscle cell function?

To investigate the relationship between GUCY1A3 expression and vascular smooth muscle cell (VSMC) function:

• Co-localization studies:

  • Use HRP-conjugated GUCY1A3 antibodies alongside smooth muscle markers (α-SMA, SM-MHC)

  • Perform immunofluorescence to determine subcellular localization

  • Evaluate expression patterns in different vascular beds and disease states

• Functional assessments correlated with expression:

  • Measure VSMC migration using wound healing or Boyden chamber assays

  • Assess proliferation rates using BrdU incorporation or Ki67 staining

  • Evaluate contractile responses to vasoconstrictors and vasodilators

  • Quantify calcium signaling in response to NO donors

• Genetic manipulation approaches:

  • Use siRNA knockdown to reduce GUCY1A3 expression

  • Overexpress GUCY1A3 using viral vectors

  • Create CRISPR-edited VSMCs with specific GUCY1A3 variants

  • Measure functional outcomes after genetic manipulation

• Pharmacological modulation:

  • Treat VSMCs with sGC stimulators or activators

  • Assess differential responses based on baseline GUCY1A3 expression

  • Combine with genetic approaches to confirm specificity

• Ex vivo and in vivo models:

  • Isolate vessels from different GUCY1A3 genotype backgrounds

  • Measure vascular reactivity in wire or pressure myography

  • Correlate vessel function with GUCY1A3 expression levels

Research has demonstrated that pharmacologic stimulation of sGC reduces migration only in VSMCs homozygous for the non-risk allele, indicating genotype-dependent functional effects . This suggests that GUCY1A3 expression levels directly impact VSMC phenotype and function in a manner relevant to vascular disease pathophysiology.

How can immunoprecipitation with GUCY1A3 antibodies identify novel protein-protein interactions?

Immunoprecipitation (IP) using GUCY1A3 antibodies is a powerful approach for discovering novel protein-protein interactions:

• Optimized IP protocol:

  • Lyse cells/tissues in non-denaturing buffers to preserve protein complexes

  • Pre-clear lysates with protein A/G beads to reduce non-specific binding

  • Incubate with GUCY1A3 antibodies (typically 2-5 μg per 500 μg protein)

  • Capture complexes with protein A/G beads

  • Wash extensively with increasingly stringent buffers

  • Elute bound proteins for downstream analysis

• Validation of known interactions:

  • Confirm co-precipitation of the β1 subunit (GUCY1B3) as positive control

  • Verify interaction with HSP90, a known chaperone for sGC

  • Assess complex formation with known pathway components

• Discovery approaches for novel interactions:

  • Perform mass spectrometry on immunoprecipitated complexes

  • Compare interactome under basal and stimulated conditions

  • Identify differential interactions in cells with GUCY1A3 variants

• Proximity-based interaction studies:

  • Combine with BioID or APEX2 proximity labeling

  • Perform proximity ligation assays to verify interactions in situ

  • Use FRET or BiFC for live-cell interaction monitoring

• Functional validation of interactions:

  • Confirm interactions using reciprocal IP

  • Perform domain mapping to identify interaction regions

  • Assess functional consequences of disrupting specific interactions

This approach can reveal novel interactions that regulate GUCY1A3 stability, localization, or activity, potentially identifying new therapeutic targets. The search results indicate that GUCY1A3 interacts with various proteins involved in its regulation, including the transcription factor ZEB1 which differentially binds to the promoter region based on rs7692387 genotype .

What are common problems with GUCY1A3 antibody applications and their solutions?

When working with GUCY1A3 HRP-conjugated antibodies, researchers may encounter several challenges:

• High background in Western blots:

  • Problem: Non-specific binding producing background noise

  • Solution: Increase blocking time (2 hours at room temperature), use 5% BSA instead of milk, increase washing steps (5× 5 minutes), and optimize antibody dilution (start with 1:500)

  • Prevention: Include 0.05% Tween-20 in all buffers and incubate primary antibody at 4°C overnight

• Weak or absent signal:

  • Problem: Insufficient protein, inactive antibody, or suboptimal detection

  • Solution: Increase protein loading (50-75 μg), use fresh antibody aliquot, extend exposure time

  • Prevention: Always include positive controls (transfected cells or tissues known to express GUCY1A3)

• Multiple bands in Western blot:

  • Problem: Non-specific binding or protein degradation

  • Solution: Verify with blocking peptide, add protease inhibitors during sample preparation

  • Prevention: Use freshly prepared samples and handle at 4°C to minimize degradation

• Inconsistent immunohistochemistry staining:

  • Problem: Variable antigen retrieval or antibody penetration

  • Solution: Standardize antigen retrieval time and temperature, extend antibody incubation

  • Prevention: Process all comparative samples in the same batch

• Cross-reactivity concerns:

  • Problem: Antibody binds to similar proteins (e.g., GUCY1A2)

  • Solution: Validate specificity using knockout/knockdown controls

  • Prevention: Select antibodies raised against unique epitopes of GUCY1A3

Data from validation studies show that properly optimized protocols can achieve specific detection of GUCY1A3 in various applications, as demonstrated by the detection of a single specific band in Western blots of cell lysates transfected with the GUCY1A3 gene .

How should researchers validate the specificity of GUCY1A3 antibodies?

Rigorous validation of GUCY1A3 antibody specificity is essential for reliable research results:

• Genetic validation approaches:

  • Test antibody on samples from GUCY1A3 knockout models

  • Use siRNA knockdown samples as negative controls

  • Employ CRISPR/Cas9-edited cell lines with specific GUCY1A3 deletions

  • Overexpress GUCY1A3 in cells with low endogenous expression

• Peptide competition assays:

  • Pre-incubate antibody with excess immunizing peptide

  • Run parallel assays with and without peptide competition

  • Specific signals should be significantly reduced or eliminated

• Multiple antibody validation:

  • Compare results using antibodies targeting different GUCY1A3 epitopes

  • Consistent results across different antibodies support specificity

  • Discrepancies may indicate non-specific binding or isoform detection

• Application-specific validation:

  • Western blot: Verify correct molecular weight (77-82 kDa)

  • IHC: Compare with mRNA expression patterns (RNAscope or ISH)

  • IP: Confirm pulled-down proteins by mass spectrometry

• Tissue expression patterns:

  • Verify higher expression in known GUCY1A3-rich tissues (vascular smooth muscle, platelets)

  • Compare expression patterns with published RNA-seq and proteomics datasets

  • Confirm cell-type specificity with co-localization studies

Published validation data for GUCY1A3 antibodies demonstrate specific detection in Western blot analysis, with clear differentiation between non-transfected and GUCY1A3-transfected cell lysates , confirming the ability to specifically recognize the target protein.

What quality control measures ensure consistent results with GUCY1A3 antibodies across experiments?

To maintain consistency across experiments using GUCY1A3 HRP-conjugated antibodies:

• Antibody storage and handling:

  • Store at -20°C in small single-use aliquots

  • Avoid repeated freeze-thaw cycles (limit to <5)

  • Keep working dilutions at 4°C and use within 24 hours

  • Monitor expiration dates (typical shelf life: 12 months)

• Standard operating procedures:

  • Develop detailed protocols for each application

  • Standardize critical parameters (antibody concentration, incubation times, temperatures)

  • Use consistent blocking reagents and buffers across experiments

  • Document lot numbers and maintain antibody validation records

• Internal controls for each experiment:

  • Include positive controls (tissues/cells known to express GUCY1A3)

  • Run negative controls (tissues lacking expression or antibody omission)

  • Use calibration standards for quantitative applications

  • Maintain a reference sample across experimental batches

• Instrument and reagent standardization:

  • Calibrate imaging equipment regularly

  • Use the same detection reagents and substrates

  • Prepare fresh buffers using consistent recipes

  • Maintain consistent exposure settings for imaging

• Data normalization strategies:

  • Use housekeeping proteins or total protein staining for normalization

  • Apply consistent analysis methods for quantification

  • Include technical replicates to assess experimental variation

  • Process all comparative samples simultaneously

Implementing these quality control measures helps ensure that observed differences in GUCY1A3 expression reflect true biological variation rather than technical artifacts, critical for studies comparing expression between different genotype groups or disease states.

How should researchers quantify and interpret GUCY1A3 expression data in genotype studies?

For accurate quantification and interpretation of GUCY1A3 expression in genotype studies:

• Quantification methodologies:

  • Use densitometry software for Western blot quantification

  • Apply background subtraction consistently across all samples

  • Normalize to validated housekeeping proteins (β-actin, GAPDH)

  • Consider total protein normalization (Ponceau S, stain-free technology) for greater accuracy

• Statistical analysis approaches:

  • Use appropriate statistical tests based on data distribution (parametric vs. non-parametric)

  • Apply ANOVA for multi-group comparisons with post-hoc tests

  • Consider mixed-effects models for repeated measures designs

  • Perform power analysis to ensure adequate sample sizes for detecting genotype effects

• Genotype grouping strategies:

  • Analyze in both additive models (dose-dependent G allele effects) and recessive models

  • Consider stratified analysis based on homozygous risk (G/G), heterozygous (G/A), and non-risk (A/A) groups

  • Account for population-specific allele frequencies in analysis

• Integration with functional data:

  • Correlate protein expression with functional outcomes

  • Develop regression models incorporating both genotype and expression data

  • Calculate expression-function ratios to assess pathway efficiency

• Interpretation frameworks:

  • Interpret expression differences in the context of pathway biology

  • Consider threshold effects in the NO-sGC-cGMP signaling cascade

  • Evaluate compensatory mechanisms that may mask expression differences

Research has demonstrated that the rs7692387 risk (G) allele is associated with approximately 20-30% lower GUCY1A3 expression levels compared to the non-risk allele, with functional consequences for platelet reactivity and vascular smooth muscle cell migration .

What methodological approaches best correlate GUCY1A3 expression with cardiovascular disease outcomes?

To effectively correlate GUCY1A3 expression with cardiovascular outcomes:

• Cohort study designs:

  • Prospective cohorts with baseline GUCY1A3 measurement and long-term follow-up

  • Case-control studies comparing expression between patients with and without events

  • Nested case-control designs within larger cohorts

  • Integration of genotype, expression, and outcome data

• Tissue selection strategies:

  • Platelets: Accessible biomarker with functional relevance

  • Peripheral blood mononuclear cells: Surrogate for vascular expression

  • Vascular biopsies: Direct assessment in target tissue when available

  • Consider tissue-specific expression patterns when interpreting results

• Multimodal assessment approaches:

  • Combine protein quantification with activity assays (cGMP production)

  • Assess downstream pathway activation markers

  • Integrate with functional assays (platelet aggregation, vasoreactivity)

  • Correlate with imaging markers of vascular disease

• Statistical and bioinformatic methods:

  • Survival analysis (Cox proportional hazards) for time-to-event outcomes

  • Machine learning approaches for complex pattern recognition

  • Mediation analysis to assess expression as mediator between genotype and outcome

  • Network analysis to position GUCY1A3 within broader pathway interactions

• Interpreting effect sizes:

  • Hazard/odds ratios per unit change in expression

  • Threshold analysis to identify clinically relevant expression levels

  • Population attributable risk calculations incorporating expression data

  • Stratified analysis by traditional risk factors

Studies have demonstrated that the GUCY1A3 rs7692387 risk (G) allele increases cardiovascular disease risk with a hazard ratio of 1.38 (95% CI: 1.08–1.78), and this effect is mediated through reduced GUCY1A3 expression and subsequent alterations in NO-sGC signaling .

How can GUCY1A3 antibodies help identify patient subgroups for personalized medicine approaches?

GUCY1A3 antibodies can facilitate personalized medicine approaches through several methodological strategies:

• Biomarker development:

  • Develop standardized immunoassays for GUCY1A3 protein quantification

  • Establish normal reference ranges across different populations

  • Define clinically relevant threshold values that predict treatment response

  • Create multiplexed assays measuring GUCY1A3 alongside other pathway components

• Treatment response prediction:

  • Stratify patients based on baseline GUCY1A3 expression

  • Correlate expression levels with response to NO pathway modulators

  • Develop predictive algorithms combining genotype and protein expression

  • Identify patients likely to benefit from aspirin therapy based on expression patterns

• Pharmacodynamic monitoring:

  • Measure changes in GUCY1A3 expression during treatment

  • Assess pathway activation using phospho-specific antibodies

  • Monitor treatment effects on GUCY1A3-dependent cellular functions

  • Adjust therapy based on molecular response markers

• Companion diagnostic development:

  • Create point-of-care tests measuring GUCY1A3 levels or activity

  • Validate predictive cutoff values in prospective clinical trials

  • Develop algorithms combining multiple biomarkers for better prediction

  • Implement in clinical decision support systems

• Novel therapeutic targeting:

  • Identify patients with deficient GUCY1A3 expression for targeted therapy

  • Develop approaches to enhance expression in risk allele carriers

  • Test sGC stimulators/activators in patients stratified by GUCY1A3 status

  • Design combination therapies addressing pathway deficiencies

Research has demonstrated that GUCY1A3 genotype significantly influences aspirin therapy outcomes, with homozygous risk allele carriers benefiting from aspirin (OR 0.79) while heterozygotes experienced adverse effects (OR 1.39) . Expression-based stratification could refine this approach beyond genotyping alone, potentially improving the precision of cardiovascular preventive therapy.

GUCY1A3 expression levels by rs7692387 genotype and tissue type

This data compilation based on research findings shows the tissue-specific variations in GUCY1A3 expression by genotype, with the most pronounced expression differences observed in vascular smooth muscle cells. The functional impact column summarizes the downstream consequences of these expression differences on NO pathway sensitivity and therapeutic response .

Technical specifications of GUCY1A3 HRP-conjugated antibodies

This table summarizes the key technical specifications of commercially available GUCY1A3 HRP-conjugated antibodies, along with the validation methods used to confirm their characteristics. These specifications provide essential guidance for researchers selecting antibodies for their experimental applications .

Effect of GUCY1A3 genotype on aspirin therapy outcomes in primary prevention

This table presents the relationship between GUCY1A3 rs7692387 genotype and aspirin therapy outcomes in primary cardiovascular disease prevention, derived from randomized controlled trials. The significant interaction (P=0.01) between genotype and aspirin effect demonstrates the potential for genotype-guided aspirin therapy in primary prevention settings .