OR8H3 Antibody

What is OR8H3 and what is its biological significance?

OR8H3 is an olfactory receptor classified as a member of the large family of G-protein-coupled receptors (GPCRs). It plays a role in the detection of specific odors, initiating a neuronal response that triggers the perception of smell. The receptor protein is encoded by a single coding-exon gene and shares a 7-transmembrane domain structure with many neurotransmitter and hormone receptors . OR8H3 is primarily involved in odorant recognition and G protein-mediated transduction of odorant signals within the olfactory system.

What are the currently available applications for OR8H3 antibodies?

Based on current research tools, OR8H3 antibodies have been validated for several applications:

These applications enable researchers to detect and analyze OR8H3 expression in various experimental contexts .

How should researchers select the appropriate OR8H3 antibody for their experiments?

When selecting an OR8H3 antibody, researchers should consider:

• Target specificity: Determine whether you need an antibody targeting a specific region (e.g., C-terminal) of OR8H3. For instance, ABIN7185373 targets the C-terminal region (AA 262-311) .

• Host species and clonality: Most available OR8H3 antibodies are rabbit polyclonal antibodies .

• Cross-reactivity profile: Some antibodies may cross-react with OR8H3 from multiple species, while others are human-specific .

• Application compatibility: Verify that the antibody has been validated for your specific application (ELISA, IF, WB) .

• Format requirements: Consider whether you need a conjugated or unconjugated antibody based on your detection system .

What are the optimal storage conditions for maintaining OR8H3 antibody activity?

To maintain optimal activity of OR8H3 antibodies:

• Store at -20°C or -80°C upon receipt.

• Avoid repeated freeze-thaw cycles as this can degrade antibody quality.

• For antibodies in liquid format (e.g., in PBS containing 50% glycerol, 0.5% BSA and 0.02% sodium azide), limited short-term storage at 4°C is acceptable.

• When working with sodium azide-containing antibodies, remember this is a hazardous substance that should be handled by trained personnel only .

How should researchers validate OR8H3 antibody specificity in their experimental system?

A robust validation protocol should include:

• Positive and negative controls: Use tissues/cells known to express or not express OR8H3.

• Western blot analysis: Verify a single band of the expected molecular weight (~36 kDa for OR8H3).

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to confirm specificity.

• Knockout/knockdown validation: Compare staining in OR8H3 knockout or knockdown samples versus wild-type.

• Cross-reactivity testing: If working with multiple species, confirm species-specific activity as documented in product datasheets.

• Secondary antibody-only control: To account for background staining from the detection system.

This systematic approach ensures that observed signals are genuinely attributable to OR8H3 .

For Western Blotting:

• Harvest cells or tissues and lyse in a buffer containing protease inhibitors.

• Centrifuge (>3000 x g) to remove debris.

• Determine protein concentration.

• Denature samples with a reducing agent at 95°C for 5 minutes.

• Load 20-50 μg of protein per lane for detection.

For Immunofluorescence:

• Fix cells or tissue sections with 4% paraformaldehyde.

• Permeabilize with 0.1-0.5% Triton X-100.

• Block with 1-5% BSA or serum.

• Incubate with OR8H3 antibody at 1:200-1:1000 dilution.

• Detect with fluorophore-conjugated secondary antibody.

For ELISA:

• Coat plates with capture antibody or antigen.

• Block with appropriate buffer.

• Add samples and standards.

• Use OR8H3 antibody at 1:10000 dilution for detection.

• Develop with appropriate substrate system.

These protocols should be optimized based on your specific research requirements .

How do AI-based approaches impact antibody design and specificity for targets like OR8H3?

Recent advances in AI technologies are transforming antibody design:

• De novo generation: AI can generate antigen-specific antibody CDRH3 sequences using germline-based templates, potentially bypassing traditional experimental approaches .

• Binding prediction: Machine learning models predict antibody-antigen binding by analyzing many-to-many relationships between antibodies and antigens, though challenges remain with out-of-distribution predictions .

• Active learning strategies: Novel active learning algorithms can improve experimental efficiency by up to 35% in antibody-antigen binding prediction, reducing the required number of experiments .

• Complementarity to traditional methods: AI approaches mimic natural antibody generation outcomes while bypassing the complexity, offering efficient alternatives to traditional experimental discovery methods .

These technologies could significantly reduce the time and resources required for developing highly specific antibodies against challenging targets like olfactory receptors .

What are the challenges in studying the ultralong CDR3H phenomenon in relation to antibody specificity for targets like OR8H3?

The study of ultralong CDR3H regions presents several challenges:

• Structural complexity: Bovine CDR3H lengths can span 5-72 residues, with those >48 residues classified as "ultralong." These structures may interact with epitopes typically inaccessible to conventional antibodies .

• Diversification mechanisms: Unlike humans and mice where immunoglobulin diversity comes from recombination, cattle achieve diversity through CDR3H length heterogeneity and somatic hypermutation independent of antigenic contact .

• Library design considerations: When designing phage display or other antibody libraries targeting OR8H3, researchers must consider CDR3H length variability to ensure comprehensive epitope coverage.

• Species-specific approaches: The structural differences between human and bovine antibodies necessitate species-specific approaches when developing antibodies against targets like OR8H3 .

Understanding these unique structural features can inform the design of novel antibodies with enhanced specificity and affinity for olfactory receptors like OR8H3 .

How can researchers differentiate between OR8H3 and closely related olfactory receptors like OR8B2/OR8B3?

Distinguishing between closely related olfactory receptors requires careful experimental design:

• Epitope selection: Target unique regions that differ between OR8H3 and OR8B2/OR8B3. Sequence alignment analysis is essential for identifying these regions.

• Antibody validation: Perform cross-reactivity studies with recombinant proteins or cells expressing only one receptor type.

• Competitive binding assays: Use peptides specific to OR8H3 or OR8B2/B3 to demonstrate antibody specificity.

• Gene editing controls: Create knockout or knockin cell lines expressing only one receptor for definitive validation.

• Sequential immunoprecipitation: Deplete samples of one receptor type before probing for the other.

The OR8B2/OR8B3 antibody (PACO03849) targets the internal region of human Olfactory receptor 8B2/3 , so researchers should be cautious when studying tissues where multiple olfactory receptors are expressed to avoid cross-reactivity issues.

What are common issues when using OR8H3 antibodies in Western blotting and how can they be resolved?

Remember that OR8H3 is a transmembrane protein, so sample preparation must preserve its native structure while allowing for efficient transfer to membranes .

How can researchers quantitatively assess OR8H3 expression levels in different tissue samples?

For quantitative assessment of OR8H3 expression:

• ELISA-based quantification: The OR8H3 ELISA Kit (ABIN1743686) offers a detection range of 50-1000 pg/mL with a minimum detection limit of 50 pg/mL and sensitivity of 1.0 pg/mL. This competitive ELISA is suitable for cell culture supernatant, plasma, serum, and tissue homogenate samples .

• RT-qPCR methodology: Design primers specific to OR8H3 mRNA for transcriptional analysis, ensuring they don't amplify highly similar family members.

• Quantitative Western blotting: Use known quantities of recombinant OR8H3 to generate a standard curve for densitometric analysis.

• Flow cytometry: For cellular expression analysis, particularly in heterogeneous samples.

• Immunohistochemistry with digital image analysis: For spatial distribution and quantitative assessment in tissue sections.

Each method has advantages and limitations, so researchers often employ multiple approaches for comprehensive quantification .

What considerations should be taken into account when using OR8H3 antibodies across different species?

When working with OR8H3 antibodies across species:

• Verify cross-reactivity profile: Check the product datasheet for validated species. Some OR8H3 antibodies work only with human samples , while others have broader reactivity including cow, dog, guinea pig, horse, mouse, pig, rabbit, and rat .

• Sequence homology assessment: Compare the OR8H3 sequence homology between your species of interest and the immunogen used to generate the antibody.

• Epitope conservation: Analyze whether the specific epitope (e.g., C-terminal region) is conserved across species.

• Validation in each species: Perform species-specific positive and negative controls.

• Dilution optimization: Optimal dilutions may vary between species; perform a dilution series when adapting to a new species.

• Detection system compatibility: Ensure secondary antibodies are appropriate for the host species of your samples.

These considerations help ensure reliable results when applying OR8H3 antibodies to comparative studies across different species .

How might advances in active learning algorithms improve antibody-antigen binding prediction for OR8H3?

Recent research has shown promising developments in active learning for antibody-antigen binding prediction:

• Efficiency improvements: Active learning strategies can reduce the number of required antigen mutant variants by up to 35% and accelerate the learning process by 28 steps compared to random baseline approaches .

• Out-of-distribution prediction: These algorithms address the challenge of predicting binding when test antibodies and antigens aren't represented in training data, which is particularly valuable for olfactory receptors with limited experimental data .

• Cost reduction: By starting with small labeled subsets and iteratively expanding datasets, active learning can significantly reduce experimental costs while maintaining prediction accuracy .

• Library-on-library approaches: Novel algorithms support many-to-many relationship analysis between antibodies and antigens, ideal for high-throughput screening of OR8H3 interactions .

These computational approaches could dramatically accelerate OR8H3 research by guiding experimental design and reducing resource requirements for discovering specific antibody-antigen interactions .

What potential role might OR8H3 play in olfactory disorders and related therapeutics?

While the search results don't directly address OR8H3's role in disorders, we can consider several research directions:

• Association with frontal sinusitis: GeneCards indicates OR8H3 is associated with frontal sinusitis, suggesting potential involvement in inflammatory nasal conditions .

• Olfactory signaling pathway: OR8H3 participates in the olfactory signaling pathway, making it relevant to disorders involving smell perception deficits .

• Therapeutic targeting: Antibodies against OR8H3 could serve as tools for studying olfactory disorders and potentially as diagnostic markers.

• Comparative studies: Research comparing OR8H3 with its important paralog OR8H2 might reveal functional redundancies or specializations relevant to disease states .

• Sensory biology applications: As noted for similar receptors like OR8B2/OR8B3, antibodies against these proteins enable detection and analysis in different cell types, making them valuable for studies in sensory biology and olfactory research .

Future research should explore these connections to develop novel diagnostic and therapeutic approaches for olfactory disorders.

What controls are essential when using OR8H3 antibodies in immunohistochemistry or immunofluorescence studies?

For rigorous immunostaining experiments using OR8H3 antibodies:

• Positive tissue control: Include tissues known to express OR8H3 (olfactory epithelium).

• Negative tissue control: Include tissues known not to express OR8H3.

• Absorption control: Pre-incubate antibody with immunizing peptide to demonstrate specificity.

• Isotype control: Use non-specific IgG from the same host species at the same concentration.

• Secondary antibody-only control: Omit primary antibody to assess background from secondary antibody.

• Endogenous peroxidase/fluorescence control: Include steps to quench endogenous signals.

• Dilution series: Test multiple antibody concentrations (1:200-1:1000 for IF) to determine optimal signal-to-noise ratio .

These controls help distinguish specific OR8H3 staining from background or non-specific binding, particularly important when studying tissues with potentially low expression levels.

How can researchers effectively design experiments to integrate OR8H3 antibody-based detection with functional studies?

An integrated experimental approach might include:

• Expression-function correlation: Combine OR8H3 antibody detection with calcium imaging or electrophysiological recordings to correlate expression levels with olfactory neuron responses.

• Co-localization studies: Use OR8H3 antibodies alongside markers for:

  • Signal transduction components (Gαolf, ACIII)

  • Neuronal maturation markers

  • Other olfactory receptors
    to understand the receptor's place in the olfactory network.

• Temporal expression analysis: Track OR8H3 expression during development or following olfactory stimulation using antibody detection at defined timepoints.

• Receptor trafficking studies: Combine OR8H3 antibodies with subcellular markers to track receptor internalization and recycling following ligand binding.

• Ligand identification: Pair antibody-based expression confirmation with functional screening to identify specific odorants that activate OR8H3.

This multifaceted approach links molecular expression patterns to physiological function, providing a more comprehensive understanding of OR8H3's role in olfaction .