rdh10b Antibody

What is RDH10 and why is it important in research?

RDH10 (Retinol dehydrogenase 10) is a strictly NAD+-dependent enzyme with multisubstrate specificity that recognizes cis-retinols as well as all-trans-retinol as substrates. It plays a crucial role in the conversion of all-trans-retinol to all-trans-retinal, which is a key step in retinoic acid synthesis and the visual cycle .

The importance of RDH10 in research stems from its involvement in:

• Retinoid metabolism in the visual cycle

• Embryonic development processes

• Potential compensation mechanisms in visual disorders such as fundus albipunctatus

Understanding RDH10 function has significant implications for developmental biology, vision research, and potential therapeutic interventions for retinal diseases .

What are the key differences between RDH10 and other retinol dehydrogenases?

RDH10 differs from other retinol dehydrogenases in several important aspects:

• Substrate specificity: While RDH10 primarily converts all-trans-retinol to all-trans-retinal, it has broader substrate specificity compared to some other RDHs. It shows no detectable activity toward 11-cis-retinol, 9-cis-retinol, and 13-cis-retinol in some contexts , but can oxidize 11-cis-retinol in the presence of CRALBP (Cellular retinaldehyde-binding protein) .

• Cofactor preference: RDH10 shows preference for NADP as a cofactor in some experimental systems , but can use both NAD+ and NADP+ as cofactors for 11-cis-RDH activity, with NAD+ conferring more robust activity .

• Tissue distribution: Unlike some other RDHs that may be more restricted in expression, RDH10 is expressed in multiple tissues including retinal pigment epithelium (RPE), Muller cells, liver, and kidney .

• Protein interactions: RDH10 physically interacts with visual cycle proteins like CRALBP and RPE65, suggesting a specific role in the visual cycle beyond its enzymatic activity .

How do I select the appropriate RDH10 antibody for my research?

Selecting the appropriate RDH10 antibody requires consideration of several factors:

• Target species: Verify the antibody's reactivity with your species of interest. Available RDH10 antibodies show reactivity with human, mouse, and rat samples, with some also demonstrating reactivity with insect models .

• Application compatibility: Different antibodies are optimized for specific applications:

  • For Western blot: Consider antibodies validated at dilutions of 1:1000-1:4000 or 1:500-1:2000

  • For immunohistochemistry: Look for antibodies validated at dilutions of 1:50-1:500

  • For immunofluorescence: Choose antibodies specifically validated for ICC/IF applications

  • For immunoprecipitation: Select antibodies validated at 0.5-4.0 µg for 1.0-3.0 mg of total protein lysate

• Antibody format: Consider whether you need unconjugated antibodies or those with specific conjugates based on your detection system .

• Validation data: Review the antibody's validation data, including Western blot bands at the expected molecular weight (~38-39 kDa) and positive controls in tissues known to express RDH10 (e.g., liver, kidney, retina) .

What are the optimal conditions for using RDH10 antibodies in Western blot applications?

For optimal Western blot results with RDH10 antibodies, consider the following methodological guidelines:

• Sample preparation:

  • Validated positive controls include HepG2 cells, A549 cells, mouse liver tissue, mouse/rat kidney tissue

  • Load 25μg protein per lane for cell lysates

  • Use appropriate lysis buffers that preserve protein structure

• Antibody dilution:

  • Primary antibody: Use at 1:1000-1:4000 dilution range or 1:500-1:2000 depending on the specific antibody

  • Secondary antibody: HRP-conjugated anti-rabbit IgG at 1:10000 dilution has been validated

• Expected results:

  • Molecular weight: Look for bands at approximately 38-39 kDa

  • The observed molecular weight may vary slightly from the calculated 38 kDa due to post-translational modifications

• Blocking conditions:

  • 3% nonfat dry milk in TBST has been validated as an effective blocking buffer

• Detection method:

  • ECL-based detection systems are suitable, with exposure times of approximately 10 seconds reported for clear visualization

How can I optimize immunohistochemistry protocols for RDH10 detection in tissue sections?

Optimizing immunohistochemistry for RDH10 detection requires careful attention to several methodological details:

• Antigen retrieval:

  • Use TE buffer pH 9.0 for optimal antigen retrieval

  • Alternative method: citrate buffer pH 6.0 may also be effective

• Antibody dilution:

  • Use antibody at 1:50-1:500 dilution, with titration recommended for each specific tissue type

• Validated tissues:

  • Mouse kidney tissue has been positively validated for IHC detection of RDH10

  • Retinal tissues are appropriate given RDH10's expression in RPE and Muller cells

• Co-localization studies:

  • Consider double immunostaining with markers for RPE65 and CRALBP, as RDH10 co-localizes with these proteins in RPE cells

• Controls:

  • Include appropriate negative controls (omitting primary antibody)

  • Consider using tissues from RDH10 knockout models as negative controls where available

What methods are effective for studying RDH10 enzymatic activity in conjunction with antibody-based detection?

Combining enzymatic activity assays with antibody-based detection provides a comprehensive understanding of RDH10 function:

• Activity assay methodology:

  • Use microsomal fractions from cells expressing RDH10 for activity measurements

  • Measure the conversion of all-trans-retinol to all-trans-retinal or 11-cis-retinol to 11-cis-retinal depending on the aspect of RDH10 function under investigation

  • Analyze retinoid profiles by HPLC for quantitative assessment

• Cofactor considerations:

  • Include both NAD+ and NADP+ in separate reaction conditions to compare activity

  • NADP+ is the preferred cofactor for all-trans retinol dehydrogenase activity in some systems

  • NAD+ confers more robust activity for 11-cis-RDH function

• Integrated approaches:

  • Combine activity assays with Western blot or immunofluorescence to correlate protein levels with enzymatic activity

  • For visual cycle studies, reconstitute the system by co-expressing RDH10 with CRALBP, RPE65, and LRAT in cell culture models

• Controls:

  • Include enzyme inhibitors specific to RDH enzymes as negative controls

  • Use purified recombinant RDH10 as a positive control for activity measurements

How can co-immunoprecipitation be used to investigate RDH10's interactions with other visual cycle proteins?

Co-immunoprecipitation (Co-IP) is a valuable technique for studying RDH10's protein-protein interactions:

• Experimental design:

  • Use RDH10 antibodies at 0.5-4.0 μg for immunoprecipitation of 1.0-3.0 mg total protein lysate

  • Target validated interacting partners including CRALBP and RPE65

  • Consider bidirectional Co-IP (pulling down with either RDH10 antibody or partner protein antibody) to confirm interactions

• Sample preparation:

  • Mouse liver tissue has been validated for successful IP of RDH10

  • For visual cycle protein interactions, primary RPE cells or appropriately transfected cell lines expressing RDH10 and partner proteins are suitable

• Controls and validation:

  • Include IgG control immunoprecipitations

  • Confirm specificity using lysates from cells with RDH10 knockdown

  • Validate interactions using complementary methods such as proximity ligation assays or FRET

• Analysis considerations:

  • Western blot for co-precipitated proteins using specific antibodies

  • Consider mass spectrometry analysis of immunoprecipitates to identify novel interacting partners

  • Correlate interaction data with functional assays to understand the biological significance of the interactions

What approaches can be used to study RDH10 localization and trafficking in cellular models?

Understanding RDH10's subcellular localization and trafficking requires specialized approaches:

• Immunofluorescence optimization:

  • Use PFA fixation (4%) followed by Triton X-100 permeabilization for A431 cells

  • Appropriate dilution: 4 μg/mL has been validated for clear visualization

• Co-localization studies:

  • Pair RDH10 antibodies with markers for endoplasmic reticulum, Golgi apparatus, and other subcellular compartments

  • For retinal cells, co-stain with RPE65 and CRALBP to validate functional interaction domains

• Live-cell imaging approaches:

  • Consider generating RDH10-fluorescent protein fusions (ensuring tag doesn't interfere with function)

  • Validate fusion protein localization using RDH10 antibodies in fixed cells

  • Use photoactivatable or photoconvertible tags to track protein movement between compartments

• Trafficking studies:

  • Employ pulse-chase experiments with protein synthesis inhibitors

  • Investigate effects of retinoid substrate availability on RDH10 localization

  • Study trafficking responses to light/dark cycles in retinal cells

How can RDH10 antibodies be used in studies investigating the role of RDH10 in retinal disease models?

RDH10 antibodies are valuable tools for studying retinal disease mechanisms:

• Expression analysis in disease models:

  • Compare RDH10 protein levels between control and disease model tissues using Western blot

  • Note that RDH10 expression levels differ between mouse strains (e.g., higher in BALB/c than C57Bl/6 mice)

  • Correlate RDH10 levels with other visual cycle proteins like RGR and RPE65

• Compensation mechanisms:

  • Investigate RDH10 expression in models of fundus albipunctatus (RDH5 deficiency)

  • Use RDH10 antibodies to detect potential upregulation as a compensatory mechanism

• Therapeutic intervention studies:

  • Monitor changes in RDH10 expression following treatment interventions

  • Correlate protein levels with functional recovery using electroretinography

• Developmental studies:

  • Track RDH10 expression during normal and abnormal retinal development

  • Correlate with retinoic acid signaling markers

What are common issues with RDH10 antibody specificity and how can they be addressed?

Addressing specificity issues with RDH10 antibodies requires systematic troubleshooting:

• Validation approaches:

  • Confirm specificity using RDH10 knockdown/knockout controls

  • Validate antibody performance in tissues known to express RDH10 (liver, kidney, retina)

  • Pre-absorb antibody with immunizing peptide to confirm specificity of signal

• Cross-reactivity considerations:

  • Be aware that RDH10 belongs to the short-chain dehydrogenase/reductase family (SDR16C4) , which has multiple members with sequence similarity

  • When possible, compare results from multiple RDH10 antibodies raised against different epitopes

• Technical optimizations:

  • Adjust antibody concentration to minimize background while maintaining specific signal

  • Optimize blocking conditions (3% nonfat dry milk in TBST has been validated)

  • Consider more stringent washing procedures if background is problematic

• Application-specific considerations:

  • For Western blots, ensure reducing conditions are appropriate

  • For IHC/IF, optimize antigen retrieval methods (TE buffer pH 9.0 or citrate buffer pH 6.0)

How should RDH10 antibodies be stored and handled to maintain optimal performance?

Proper storage and handling of RDH10 antibodies is essential for maintaining their performance:

• Storage conditions:

  • Store at -20°C for long-term storage

  • For short-term use, store at 4°C

  • Antibodies are typically stable for one year after shipment when properly stored

• Aliquoting considerations:

  • Aliquot antibodies to avoid repeated freeze-thaw cycles

  • For antibodies stored at -20°C with 50% glycerol, aliquoting may be unnecessary

• Buffer composition effects:

  • Be aware that some antibodies are supplied in PBS with 0.02% sodium azide and 50% glycerol (pH 7.3)

  • Others may contain 2% sucrose and 0.09% sodium azide

  • Note that glycerol may interfere with some downstream applications and should be added with caution

• Concentration and formulation:

  • Antibody concentrations may vary (e.g., 0.5 mg/ml)

  • BSA-free formulations are available for applications where BSA might interfere

What approaches can resolve contradictory results when using different RDH10 antibodies?

When faced with contradictory results using different RDH10 antibodies, consider these resolution strategies:

• Epitope mapping:

  • Compare the immunogens used to generate each antibody:

    • Some are generated against specific peptide sequences (e.g., N-terminal peptide QSNEETAGMVRHIYRDLEAADAAALQAGNGEEEILPHCNLQVFTYTCDVG)

    • Others target recombinant protein fragments (e.g., within Human RDH10 aa 150 to C-terminus)

    • RDH10 fusion proteins may be used as immunogens

• Validation with complementary techniques:

  • Confirm protein expression using RNA analysis methods (RT-PCR, RNA-seq)

  • Use functional assays to validate protein activity where antibody results are contradictory

  • Consider mass spectrometry approaches for definitive protein identification

• Controls and standards:

  • Use recombinant RDH10 protein standards to compare antibody binding characteristics

  • Include appropriate positive controls (e.g., HepG2 cells, A549 cells, mouse liver tissue)

  • Implement genetic approaches (siRNA knockdown, CRISPR knockout) to validate specificity

• Systematic comparison:

  • Test multiple antibodies side-by-side under identical conditions

  • Document differences in observed molecular weight (expected ~38-39 kDa)

  • Consider post-translational modifications that might affect epitope recognition

How can RDH10 antibodies be integrated into multi-omics research approaches?

Integrating RDH10 antibodies into multi-omics research provides comprehensive insights:

• Proteomics integration:

  • Use RDH10 antibodies for immunoprecipitation followed by mass spectrometry to identify interacting proteins

  • Correlate RDH10 protein levels (measured by quantitative Western blot) with global proteome changes

  • Employ phospho-specific antibodies (if available) to analyze post-translational modification states

• Transcriptomics correlation:

  • Compare RDH10 protein levels with RDH10 mRNA expression across tissues and conditions

  • Investigate potential post-transcriptional regulation by correlating protein and mRNA levels

• Metabolomics connections:

  • Correlate RDH10 protein levels with retinoid metabolite profiles measured by HPLC

  • Link RDH10 expression to broader metabolic network changes

• Spatial analysis:

  • Use RDH10 antibodies in spatial proteomics approaches such as imaging mass cytometry

  • Correlate spatial distribution with spatial transcriptomics data

What are the considerations for using RDH10 antibodies in single-cell analysis techniques?

Adapting RDH10 antibodies for single-cell analysis requires specific technical considerations:

• Flow cytometry optimization:

  • Evaluate antibody performance in intracellular staining protocols

  • Optimize fixation and permeabilization conditions for intracellular enzyme detection

  • Consider dual staining with markers of cell identity (e.g., RPE or Muller cell markers)

• Single-cell Western approaches:

  • Validate antibody performance at the sensitivity required for single-cell analysis

  • Optimize lysis conditions to preserve RDH10 epitopes while ensuring efficient extraction

• Single-cell proteomics:

  • Evaluate antibody specificity in highly multiplexed antibody panels

  • Consider using RDH10 antibodies in CyTOF or CODEX imaging if suitable metal conjugates can be prepared

• Spatial resolution:

  • Optimize RDH10 antibodies for super-resolution microscopy techniques

  • Evaluate performance in tissue clearing and 3D imaging protocols for whole-tissue analysis

How can computational approaches enhance the interpretation of RDH10 antibody-based experimental data?

Computational methods can significantly enhance RDH10 antibody data interpretation:

• Image analysis algorithms:

  • Implement automated segmentation for quantifying RDH10 subcellular localization

  • Use colocalization analysis software to quantify interaction with partner proteins like CRALBP and RPE65

• Network analysis:

  • Integrate RDH10 protein interaction data from co-IP studies into protein-protein interaction networks

  • Map RDH10 to known retinoid metabolism and visual cycle pathways

• Structural biology integration:

  • Use epitope information from antibodies to constrain protein structure predictions

  • Model potential conformational changes upon substrate binding or protein interaction

• Machine learning applications:

  • Train neural networks to recognize RDH10 expression patterns in tissue samples

  • Develop predictive models for RDH10 function based on expression patterns and interaction data