GUCY1A1 Antibody

What is GUCY1A1 and what is its biological function?

GUCY1A1 (also known as GUCY1A3, GCS-alpha-1, GCS-alpha-3) is the alpha-1 subunit of soluble guanylate cyclase (sGC), a key enzyme in the nitric oxide (NO)/cGMP signaling pathway . This protein interacts with a beta subunit (GUCY1B1) to form the functional guanylate cyclase enzyme that catalyzes the conversion of GTP to 3',5'-cyclic GMP and diphosphate . The NO-sGC-cGMP signaling pathway plays critical roles in cardiovascular physiology, and variants in GUCY1A1 have been genome-wide significantly associated with coronary artery disease risk .

What applications are GUCY1A1 antibodies typically used for in research?

GUCY1A1 antibodies are used in multiple experimental applications including:

Research shows these applications have been successfully employed to study GUCY1A1 expression patterns, protein interactions, and signaling mechanisms in various experimental models .

How do I select the appropriate GUCY1A1 antibody for my specific research application?

Selection should be based on:

• Target epitope: Consider antibodies targeting different regions (N-terminal, C-terminal, or specific internal domains) based on your research question. For example, some studies have used antibodies targeting amino acids 22-214 , 269-300 , or 374-423 .

• Host species and clonality: Available options include:

  • Mouse monoclonal antibodies (e.g., clones 3G6B2, 2H1)

  • Rabbit polyclonal antibodies

  • Rabbit monoclonal antibodies (e.g., clone EPR12270)

• Validated applications: Confirm the antibody has been validated for your specific application. For instance, if performing co-immunoprecipitation studies of protein interactions as in Hochheiser et al. (2016), select antibodies validated for IP .

• Species reactivity: Ensure cross-reactivity with your experimental model (human, mouse, rat) .

• Published validation data: Review literature citations and validation images before selection .

What are the recommended protocols for validating a new GUCY1A1 antibody?

A comprehensive validation should include:

• Positive and negative controls: Test on tissues known to express and not express GUCY1A1. Hepatic stellate cells express GUCY1A1, while hepatocytes, LSECs, and Kupffer cells do not .

• Western blot validation: Confirm detection of the expected 77.5 kDa band . Compare with recombinant protein controls and/or cell lines with known expression levels.

• Knockdown/knockout controls: Test antibody specificity using siRNA knockdown or genetic knockout samples. This approach was used to validate GUCY1A1 antibodies in multiple studies .

• Antibody comparison: Test multiple antibodies targeting different epitopes to verify consistent results.

• Reporter validation: Consider using genetic reporter systems like the Gucy1a1-EGFP reporter mice to validate antibody specificity, as demonstrated in research where GUCY1A1 antibody staining colocalized with EGFP signal .

How can I troubleshoot weak or nonspecific GUCY1A1 antibody signals in Western blots?

Common issues and solutions include:

• Low expression levels: GUCY1A1 expression varies across tissues and can be regulated by factors like Notch signaling . For tissues with low expression:

  • Increase protein loading amount

  • Use more sensitive detection methods

  • Consider concentrating your protein sample

  • Use enrichment techniques like immunoprecipitation before blotting

• Nonspecific binding: To reduce background:

  • Optimize blocking conditions (try 5% BSA instead of milk)

  • Increase washing steps duration and number

  • Optimize antibody dilution (test range from 1:500 to 1:2000)

  • Consider using monoclonal antibodies which often have higher specificity

• Protein degradation: GUCY1A1 (77.5 kDa) may degrade during sample preparation:

  • Add protease inhibitors to all buffers

  • Keep samples cold throughout preparation

  • Avoid repeated freeze-thaw cycles

  • Consider fresh samples rather than archived ones

• Heterodimer detection issues: Since functional sGC requires both α and β subunits, consider detecting both GUCY1A1 and GUCY1B1 to confirm the presence of the complete enzyme complex .

How do expression levels of GUCY1A1 vary across different cell types and experimental conditions?

Research has revealed significant variations in GUCY1A1 expression:

• Cell type variations:

  • Expressed in hepatic stellate cells but not in hepatocytes, LSECs, or Kupffer cells

  • Detected in brain cortex and lung at protein level

  • Expression levels differ between NE (neuroendocrine) and Non-NE cell subpopulations in cancer models

• Disease associations:

  • Upregulated during small cell lung cancer (SCLC) progression

  • Associated with chemoresistance mechanisms in cancer

  • Expression is altered in metastatic prostate cancer compared to primary tumors

• Regulatory factors:

  • Notch signaling regulates GUCY1A1 expression; N1ICD overexpression upregulates GUCY1A1

  • Age affects expression levels; significantly higher expression in juvenile mesenteric arteries compared to aged vessels

  • Genetic variants (rs7692387) affect expression levels in blood and correlate with disease risk

• Experimental conditions to consider:

  • Expression changes with NO donor treatments

  • Pharmacological sGC stimulation can alter expression and release patterns

  • Notch pathway inhibitors (DAPT, DBZ) reduce expression

How can GUCY1A1 antibodies be used to investigate the relationship between sGC signaling and disease pathophysiology?

Advanced research applications include:

• Genetic risk assessment: GUCY1A1 antibodies can help validate the functional impact of genetic variants associated with disease risk. For instance, researchers found that individuals homozygous for the rs7692387 risk variant had lower GUCY1A1 expression levels, which correlated with altered platelet function and atherosclerosis risk .

• Mechanistic disease studies: In cancer research, GUCY1A1 antibodies have been used to demonstrate that sGC upregulation is a mechanism of acquired chemoresistance in small cell lung cancer . By combining antibody-based detection with functional assays, researchers established connections between expression levels and drug resistance.

• Cell-specific pathway analysis: Using co-immunofluorescence techniques with GUCY1A1 antibodies and other pathway markers (like HES1 for Notch signaling), researchers have identified cell-specific regulation mechanisms . This approach revealed that Non-NE cells show upregulation of both Notch signaling and GUCY1A1 expression.

• ChIP-qPCR experiments: GUCY1A1 antibodies have been used in chromatin immunoprecipitation experiments to demonstrate direct binding of transcription factors (like N1ICD) to the GUCY1A1 promoter, establishing it as a direct Notch target gene .

• Prognostic marker evaluation: In tumor microarray studies, GUCY1A1 antibodies helped assess whether expression levels correlate with disease stage and clinical outcomes, though in some cancer types no significant associations were found .

What are the key considerations when studying GUCY1A1 in complex heterodimeric sGC complexes?

Important methodological considerations include:

• Subunit co-detection: Since functional sGC requires both α and β subunits (GUCY1A1 and GUCY1B1), it's critical to detect both subunits to assess functional enzyme presence. Research shows that these subunits may be differentially regulated; for example, in prostate cancer progression, GUCY1A1 was consistently downregulated in metastatic disease while GUCY1B1 showed variable patterns .

• Heterodimer isolation techniques: Consider using:

  • Co-immunoprecipitation with antibodies against either subunit

  • Size-exclusion chromatography to isolate the intact complex

  • Native PAGE conditions to preserve protein-protein interactions

• Activity correlation: Combine antibody detection with functional assays measuring cGMP production to establish correlations between protein expression and enzymatic activity. For example, ex vivo platelet studies showed that genetic variants affecting GUCY1A1 expression also impacted platelet aggregation inhibition by NO donors and phosphodiesterase inhibitors .

• Regulatory mechanisms: Consider that the α and β subunits can be differentially regulated. For instance, overexpression of N1ICD led to upregulation of GUCY1A1 without changing GUCY1B1 levels in certain cell types , suggesting distinct regulatory mechanisms for each subunit.

• Subcellular localization: Use fractionation techniques combined with immunoblotting or immunofluorescence microscopy to assess whether the subunits properly colocalize, as mislocalization could impact signaling efficiency even when both subunits are expressed .

How can I interpret contradictory GUCY1A1 expression data across different experimental models or disease states?

When facing contradictory data:

• Consider cell-type specificity: Expression patterns may differ dramatically between cell types. For example, GUCY1A1 expression was exclusively detected in hepatic stellate cells but not in other hepatic cell populations .

• Analyze temporal dynamics: GUCY1A1 upregulation may be associated with acquired (rather than inherent) disease mechanisms, as seen in chemoresistance development . The timing of sample collection could therefore greatly impact results.

• Assess genetic variants: Genetic polymorphisms affect GUCY1A1 expression and function. The rs7692387 variant is associated with lower GUCY1A1 mRNA levels , which could explain contradictory results if genotypes aren't controlled for.

• Evaluate experimental technique differences: Different antibodies target distinct epitopes, which may be differentially accessible in certain protein conformations or interactions. Compare antibody target regions when integrating data from multiple sources.

• Consider disease stage heterogeneity: In prostate cancer research, GUCY1A1 levels differed between primary and metastatic samples, suggesting disease progression affects expression . Similar stage-dependent differences might explain contradictions in other disease models.

• Examine age-related influences: Research shows age significantly affects GUCY1A1 expression, with juvenile tissues showing higher levels than aged tissues . Age differences in experimental models could contribute to contradictory findings.

What are the optimal immunohistochemistry protocols for detecting GUCY1A1 in different tissue types?

Optimized IHC protocols should consider:

• Tissue fixation and processing:

  • For paraffin sections: 10% neutral buffered formalin fixation for 24 hours

  • For frozen sections: OCT embedding after brief fixation (4% PFA for 1-2 hours)

  • Antigen retrieval methods: Heat-induced epitope retrieval in citrate buffer (pH 6.0) is typically effective

• Antibody selection and dilution:

  • For FFPE sections: 1:200-1:1000 dilution range is recommended

  • For frozen sections: Lower dilutions (1:100-1:200) may be optimal

  • Consider antibody validation in your specific tissue type before proceeding

• Detection systems:

  • For low expression tissues: Use amplification systems like tyramide signal amplification

  • For co-localization studies: Use fluorescent secondary antibodies for multiplexing

• Controls to include:

  • Positive control: Lung tissue shows reliable GUCY1A1 expression

  • Negative control: Hepatocytes lack GUCY1A1 expression

  • Antibody controls: Include secondary-only and isotype controls

• Tissue-specific considerations:

  • In vascular tissue: GUCY1A1 detection may require special attention to elastic tissue autofluorescence

  • In cancer samples: Consider tumor heterogeneity and include adjacent normal tissue

What experimental approaches can determine if genetic variants affect GUCY1A1 protein expression and function?

Comprehensive approaches include:

• Genotype-expression correlation:

  • Quantify GUCY1A1 mRNA using qPCR in samples with different genotypes

  • Measure protein levels via Western blot or ELISA across genotyped samples

  • Research has shown individuals homozygous for the rs7692387 risk variant had significantly lower whole-blood GUCY1A1 mRNA levels

• Reporter gene assays:

  • Create constructs with different alleles driving reporter expression

  • Studies demonstrated significantly lower GUCY1A1 promoter activity for constructs carrying the risk allele

• Chromatin immunoprecipitation:

  • Assess transcription factor binding differences between alleles

  • Research identified differential binding of ZEB1 transcription factor to risk vs. non-risk alleles using ChIP-qPCR

• Functional assays:

  • Ex vivo platelet studies showed enhanced inhibition of ADP-induced platelet aggregation by NO donors in non-risk allele carriers

  • Vascular smooth muscle cell migration was reduced by sGC stimulation only in cells homozygous for the non-risk allele

• Animal models:

  • The Hybrid Mouse Diversity Panel showed correlation between GUCY1A1 expression levels and reduced atherosclerosis in the aorta

  • Knockout mice models have revealed that functional loss of sGC in platelets contributes to atherosclerotic plaque formation

How are GUCY1A1 antibodies being used in emerging therapeutic research areas?

Recent advances include:

• Pharmacological sGC stimulation studies:

  • GUCY1A1 antibodies help monitor target engagement in studies evaluating sGC stimulators

  • Research demonstrated that pharmacological sGC stimulation increased platelet angiopoietin-1 release in vitro and reduced leukocyte recruitment and atherosclerotic plaque formation in atherosclerosis-prone Ldlr−/− mice

• Age-related vascular dysfunction:

  • GUCY1A1 antibodies have revealed age-dependent changes in sGC expression and function

  • Studies show expression levels of GUCY1A1 were significantly higher in juvenile mesenteric arteries compared to aged vessels, contributing to vascular smooth muscle dysfunction with aging

• Cancer resistance mechanisms:

  • GUCY1A1 antibodies help track the role of sGC signaling in chemoresistance

  • Research has established that sGC subunits are upregulated during SCLC progression and that GUCY1B1 upregulation is a mechanism of acquired chemoresistance

• Notch pathway interactions:

  • GUCY1A1 antibodies are being used to study cross-talk between signaling pathways

  • Studies have confirmed that sGC subunit expression in SCLC is regulated by Notch signaling through direct binding of N1ICD to promoter regions of GUCY1A1

• Precision medicine applications:

  • GUCY1A1 antibodies help stratify patients based on expression levels

  • Research in carriers of GUCY1A1 risk alleles showed reduced platelet angiopoietin-1 release, suggesting potential for personalized therapeutic approaches

What methodological advances have improved the specificity and sensitivity of GUCY1A1 detection?

Recent technical improvements include:

• Monoclonal antibody development:

  • Newer monoclonal antibodies like rabbit recombinant clone EPR12270 offer improved specificity

  • Clone-specific validation across multiple applications allows for more reliable detection

• Conjugated antibody formats:

  • Directly conjugated GUCY1A1 antibodies (HRP, FITC, biotin) enable more sensitive detection and reduce background in multiplex applications

  • These formats eliminate secondary antibody cross-reactivity issues

• Single-cell analysis techniques:

  • GUCY1A1 antibodies have been incorporated into single-cell transcriptomic validation studies

  • This approach confirmed cell-type specific expression patterns, such as exclusive expression in hepatic stellate cells

• Genetic reporter validation systems:

  • Gucy1a1-EGFP reporter mice provide powerful validation tools for antibody specificity

  • Studies demonstrated that GUCY1A1 antibody completely colocalized with EGFP signal, confirming specificity

• Combined protein-RNA detection methods:

  • Integrating antibody-based protein detection with RNA detection provides multi-level validation

  • This approach has confirmed transcriptional regulation mechanisms of GUCY1A1 expression across different experimental models

How can GUCY1A1 antibodies be integrated into multi-omics research approaches?

Integrated research strategies include:

• Proteogenomic correlation:

  • Combine genomic variants data with antibody-based protein quantification

  • Research linking rs7692387 variant with differential GUCY1A1 expression demonstrates this approach

• Transcriptomics validation:

  • Use antibodies to confirm protein-level changes identified in RNA-seq experiments

  • Single-cell transcriptomic findings of cell-type specificity were confirmed with GUCY1A1 antibodies

• Epigenetic regulation studies:

  • Combine ChIP-seq approaches with antibody-based protein detection

  • Research demonstrating N1ICD binding to GUCY1A1 promoter regions illustrates this integration

• Signaling pathway mapping:

  • Use phospho-specific antibodies alongside GUCY1A1 detection to map pathway activation

  • Correlate NO-sGC-cGMP pathway components with downstream effects using multi-antibody approaches

• Protein-metabolite correlations:

  • Combine GUCY1A1 protein detection with cGMP measurements

  • Studies linking sGC protein levels to functional cGMP production demonstrate this approach

What considerations are important when using GUCY1A1 antibodies across different species models?

Key cross-species considerations include:

• Epitope conservation assessment:

  • Evaluate sequence homology between human, mouse, and rat GUCY1A1 in the antibody target region

  • Some antibodies target highly conserved regions and work across species (human/mouse/rat) , while others are species-specific

• Validation requirements:

  • Perform separate validation for each species rather than assuming cross-reactivity

  • Include appropriate positive and negative controls from each species

• Application-specific optimization:

  • Dilution requirements may differ between species even for cross-reactive antibodies

  • Tissue processing protocols may need species-specific modifications

• Result interpretation differences:

  • Expression patterns and regulation mechanisms may vary between species

  • For example, age-related changes in GUCY1A1 expression in mouse models may not directly translate to human aging patterns

• Genetic model considerations:

  • When using GUCY1A1 antibodies in transgenic models, confirm the modification doesn't affect antibody binding

  • Reporter systems like Gucy1a1-EGFP mice provide valuable controls for antibody validation across species