HSD17B4 Antibody

What are the key considerations when selecting an HSD17B4 antibody for research applications?

When selecting an HSD17B4 antibody, researchers should consider several critical factors:

• Epitope location: Antibodies targeting different domains of HSD17B4 will detect different forms of the protein. For example, antibodies targeting the N-terminal region (5-91aa) will recognize both the full-length protein and the processed 35 kD dehydrogenase domain fragment .

• Species reactivity: Confirm cross-reactivity with your species of interest. Many commercial antibodies react with human, mouse, and rat HSD17B4 .

• Application compatibility: Validate that the antibody is suitable for your intended application. Common applications include Western blot (WB), immunohistochemistry (IHC), immunofluorescence (IF), and immunocytochemistry (ICC) .

• Clonality: Monoclonal antibodies offer higher specificity but limited epitope recognition, while polyclonal antibodies provide broader detection but potential cross-reactivity issues .

• Validation data: Review the manufacturer's validation data for your specific application and tissue/cell type .

How should researchers validate HSD17B4 antibody specificity before experimental use?

Proper validation of HSD17B4 antibodies should include:

• Positive and negative controls: Use tissue known to express HSD17B4 (liver, testis) as positive controls and tissues with minimal expression as negative controls .

• Knockdown/knockout validation: Compare staining/band intensity between wild-type and HSD17B4-knockdown or knockout samples to confirm specificity .

• Multiple antibody comparison: Use antibodies from different sources or targeting different epitopes to confirm consistent results .

• Expected molecular weight verification: The full-length HSD17B4 protein is approximately 80 kDa, with processed fragments at ~35 kDa (dehydrogenase domain) .

• Subcellular localization confirmation: HSD17B4 should show peroxisomal localization in immunofluorescence assays .

What is the proper reconstitution and storage protocol for lyophilized HSD17B4 antibodies?

For optimal performance of lyophilized HSD17B4 antibodies:

• Reconstitution: Add 100 μL of distilled water to achieve a final concentration of approximately 1 mg/mL .

• Secondary desalting: For conjugation experiments, an additional round of desalting is recommended (e.g., using Zeba Spin Desalting Columns, 7KMWCO) .

• Storage temperature: Store reconstituted antibody at 4°C for short-term use (one month) or aliquot and store at -20°C for longer periods (up to 12 months) .

• Avoid freeze-thaw cycles: Multiple freeze-thaw cycles significantly reduce antibody activity .

• Buffer consideration: The original buffer is typically 1X PBS, pH 7.3, with 8% trehalose as a stabilizer .

What are the optimal dilution ratios for HSD17B4 antibodies in different experimental applications?

Based on published protocols, the recommended dilution ratios for HSD17B4 antibodies vary by application:

Researchers should always perform optimization experiments for their specific samples and conditions, starting with the manufacturer's recommended dilutions and adjusting as needed for optimal signal-to-noise ratio .

How can researchers troubleshoot weak or absent HSD17B4 signal in Western blot applications?

When troubleshooting weak or absent HSD17B4 signal in Western blots:

• Sample preparation: Ensure proper cell lysis and protein extraction, especially from peroxisomes. Use peroxisome isolation techniques if necessary .

• Loading control: Verify total protein loading using housekeeping proteins and consider using peroxisomal markers like PMP70 as specific compartment controls .

• Protein transfer efficiency: Check transfer efficiency with reversible staining methods like Ponceau S before immunoblotting.

• Antibody incubation conditions: Optimize primary antibody concentration and incubation time (typically overnight at 4°C for HSD17B4) .

• Detection system: Consider using enhanced chemiluminescence (ECL) systems for greater sensitivity .

• Epitope accessibility: If HSD17B4 is dimerized or in complexes, denature samples thoroughly (95°C for 5 minutes in SDS sample buffer) .

• Molecular weight verification: For full-length HSD17B4, look for a band at approximately 80 kDa; processed forms appear at ~35 kDa .

What protocol modifications are needed for detecting disease-associated variants of HSD17B4?

For detecting disease-associated HSD17B4 variants:

• Mutation-specific considerations: Some mutations like p.Ala175Thr affect protein stability without altering mRNA levels, requiring protein-level rather than transcript-level detection methods .

• Dimerization analysis: Use Blue Native PAGE (BN-PAGE) to assess dimerization defects, as disease-causing mutations often impact the ability of HSD17B4 to form functional dimers .

• Subcellular localization: Employ co-immunofluorescence with peroxisomal markers to detect mislocalization of mutant HSD17B4 .

• Antibody selection: Choose antibodies targeting epitopes remote from the mutation site, as mutations may disrupt antibody binding .

• Controls: Include samples with known mutations for comparison, particularly when assessing subtle differences in protein levels or processing .

• Fibroblast analysis: Patient-derived fibroblasts offer an excellent model system for analyzing HSD17B4 variants and their functional consequences .

How can HSD17B4 methylation be accurately measured as a predictive biomarker in HER2-positive breast cancer?

For accurate measurement of HSD17B4 methylation as a predictive biomarker:

• Sample preparation: Use laser capture microdissection to isolate pure cancer cell populations, avoiding contamination with stromal or immune cells .

• Methylation analysis platforms: Employ Infinium 450K arrays or targeted bisulfite sequencing focusing on the transcriptional start site of the major HSD17B4 variant .

• Normalization and controls: Include appropriate normal tissue controls and use methylation-specific reference genes for normalization .

• Threshold determination: Establish clear methylation thresholds that correlate with clinical response to HER2-directed therapy .

• Validation approach: Perform multi-step validation using independent patient cohorts to confirm predictive value .

• Combined biomarkers: Consider analyzing estrogen receptor status alongside HSD17B4 methylation, as the combination shows higher positive predictive value (80%) for pathological complete response .

• Longitudinal monitoring: HSD17B4 methylation can be monitored throughout treatment to assess response to therapy .

What are the optimal methods for measuring HSD17B4 protein levels in D-bifunctional protein deficiency diagnosis?

For accurate diagnosis of D-bifunctional protein deficiency:

• Tissue selection: Analyze patient-derived fibroblasts as the primary tissue for assessment .

• Protein quantification: Use Western blot analysis to measure both full-length HSD17B4 (80 kDa) and the processed 35 kDa dehydrogenase domain fragment .

• mRNA analysis: Perform RT-qPCR to distinguish between transcriptional and post-transcriptional defects .

• Peroxisomal markers: Compare HSD17B4 levels to peroxisomal membrane proteins (e.g., PMP70) to assess relative abundance in peroxisomes .

• Dimerization assessment: Use BN-PAGE to evaluate the formation of functional HSD17B4 dimers, which is often impaired in disease states .

• Severity correlation: Compare CADD scores of identified mutations with protein expression levels to estimate disease severity and age of onset .

• Controls: Include age-matched control samples and consider the three clinical subtypes (infant-onset, juvenile-onset, and adult-onset) when interpreting results .

How should researchers design experiments to investigate the role of HSD17B4 in ciliopathy development?

When investigating HSD17B4's role in ciliopathy:

• Cell models: Utilize both patient-derived fibroblasts and HSD17B4-knockdown/knockout cell lines (like RPE and SH-SY5Y cells) for comparative analyses .

• Primary cilia assessment: Perform immunostaining for cilia markers (e.g., ARL13B) to quantify:

  • Percentage of ciliated cells

  • Ciliary length

  • Ciliary morphology

• Signaling pathway analysis: Evaluate ciliary-dependent signaling, particularly:

  • Smad2/3-mediated TGF-β signaling

  • GLI2-mediated Sonic hedgehog (Shh) pathway

• Animal models: Use Hsd17b4-knockout mice to study in vivo manifestations of ciliopathy, including:

  • Growth retardation

  • Organ-specific pathologies

  • Survival rates

• Rescue experiments: Perform complementation assays with wild-type HSD17B4 to confirm causality of observed ciliary defects .

• Mechanistic investigations: Explore the molecular link between peroxisomal dysfunction and ciliogenesis impairment through interactome studies .

How does phosphatidylserine regulate the peroxisomal localization of HSD17B4, and what techniques can detect this interaction?

The regulation of HSD17B4 localization by phosphatidylserine (PS) involves:

• Interaction assessment: Use binding assays with biotin-PS and streptavidin-conjugated magnetic beads (SCMBs) to detect direct interaction between HSD17B4 and PS .

• Calcium dependence: Test the effect of calcium by adding 2.5 mM Ca²⁺ or 10 µM EGTA to binding assays .

• Domain mapping: Express individual domains of HSD17B4 (hydroxyacyl-CoA dehydrogenase domain, enoyl-CoA hydratase domain, SCP2-like domain) as GST fusion proteins to identify which region binds PS .

• Competition assays: Use potential competitors such as glycerol 3-phosphate, phospho-L-serine, phospho-D-serine, DPPC, DOPS, or liposomes to test binding specificity .

• Topological relevance: Compare binding with PS-coated styrene beads versus liposomes to assess if membrane topology affects interaction .

• Subcellular localization: Employ co-immunofluorescence of HSD17B4 with peroxisomal markers (Catalase, Pmp70) to visualize localization changes in response to PS manipulation .

What techniques are most effective for evaluating HSD17B4 dimerization status and its correlation with enzymatic activity?

For assessing HSD17B4 dimerization and its functional consequences:

• Blue Native PAGE (BN-PAGE): This non-denaturing electrophoresis technique preserves native protein complexes and can detect dimerized HSD17B4 (~160 kDa) .

• Cross-linking assays: Chemical cross-linking followed by SDS-PAGE can stabilize transient dimers for detection.

• Size exclusion chromatography: This technique separates proteins based on size, allowing isolation and quantification of monomeric versus dimeric HSD17B4.

• Structural modeling: In silico analysis of mutations can predict their impact on dimerization interfaces, as demonstrated with the p.Ala175Thr mutation .

• Correlation with activity: Measure enzymatic activities (dehydrogenase and hydratase) in parallel with dimerization status to establish functional correlations .

• Patient-derived samples: Fibroblasts from patients with HSD17B4 mutations show significantly reduced levels of dimerized protein (~40% of controls) that correlate with disease severity .

• Microscopy approaches: Förster resonance energy transfer (FRET) or proximity ligation assays can visualize protein-protein interactions in situ.

What are the methodological considerations for detecting HSD17B4 in complex tissue samples with varying expression levels?

When analyzing HSD17B4 in complex tissues:

• Tissue processing optimization:

  • For IHC: Heat-mediated antigen retrieval in EDTA buffer (pH 8.0) significantly improves detection

  • For IF: Detergent permeabilization must be optimized to access peroxisomal proteins

• Signal amplification strategies:

  • For low-expression tissues: Consider tyramide signal amplification (TSA) or polymer-based detection systems

  • For Western blot: Extended exposure times and enhanced chemiluminescence reagents improve sensitivity

• Quantification approaches:

  • Use digital image analysis with appropriate standards

  • Normalize to peroxisomal markers rather than general housekeeping proteins

  • Consider relative quantification against multiple reference tissues

• Multi-parameter analysis:

  • Combine protein detection with mRNA analysis to distinguish transcriptional from post-transcriptional changes

  • Use multiplex approaches to simultaneously detect HSD17B4 and marker proteins

• Expression pattern considerations:

  • HSD17B4 is widely expressed across tissues but with variable levels

  • Establish tissue-specific baseline expression before interpreting pathological changes

  • Consider age-dependent expression patterns when analyzing developmental samples

How can researchers effectively study the relationship between HSD17B4 and primary cilia formation in neurological disorders?

For investigating HSD17B4's role in neurological ciliopathies:

• Cellular models:

  • Patient-derived fibroblasts carrying HSD17B4 mutations (e.g., c.422_423delAG)

  • Neuronal cell lines (SH-SY5Y) with CRISPR-Cas9 knockout of HSD17B4

  • Retinal pigment epithelial (RPE) cells with siRNA knockdown of HSD17B4

• Ciliogenesis assessment:

  • Immunofluorescence staining for ARL13B to visualize primary cilia

  • Quantitative analysis of:

    • Percentage of ciliated cells

    • Ciliary length measurements

    • Ciliary morphology alterations

• Signaling pathway evaluation:

  • Western blot or immunofluorescence for phosphorylated Smad2/3 (TGF-β pathway)

  • GLI2 nuclear translocation assays (Shh pathway)

  • Reporter assays for pathway activation

• In vivo modeling:

  • Phenotypic characterization of Hsd17b4-knockout mice

  • Tissue-specific analyses focusing on neurological tissues

  • Correlation of ciliary defects with neurological symptoms

• Mechanistic investigations:

  • Peroxisome-cilia crosstalk analysis

  • Metabolic profiling to identify intermediates affecting ciliogenesis

  • Rescue experiments with wild-type HSD17B4 or downstream metabolites

What approaches can researchers use to investigate HSD17B4 methylation as a response biomarker during HER2-directed therapy?

For monitoring HSD17B4 methylation during therapy:

• Longitudinal sampling protocols:

  • Serial liquid biopsies (circulating tumor DNA)

  • Sequential core biopsies at defined treatment timepoints

  • Post-treatment surgical specimen analysis

• Methylation detection methods:

  • Digital droplet PCR for methylation-specific detection

  • Next-generation sequencing of bisulfite-converted DNA

  • Methylation-specific high-resolution melting analysis

• Threshold determinations:

  • Establish methylation cutoffs predictive of treatment response

  • Determine rate-of-change parameters indicating favorable outcomes

  • Identify methylation patterns associated with resistance development

• Multi-marker integration:

  • Combine HSD17B4 methylation with estrogen receptor status

  • Correlate with imaging-based response criteria (RECIST)

  • Integrate with other established biomarkers

• Clinical trial design considerations:

  • Prospective validation in trials like the PASSION trial (UMIN000028065)

  • Stratification of patients based on baseline methylation status

  • Adaptive designs allowing treatment modifications based on methylation changes

How can researchers differentiate between post-translational modifications and mutations when analyzing aberrant HSD17B4 protein patterns?

To distinguish between mutations and post-translational modifications:

• Comprehensive analysis workflow:

  • Parallel genomic sequencing and protein analysis

  • Mass spectrometry to identify post-translational modifications

  • Targeted western blotting with modification-specific antibodies

• Mutation-specific approaches:

  • Exome or targeted gene sequencing to identify coding variants

  • mRNA expression analysis using RT-qPCR to detect transcript levels

  • In silico prediction of mutation effects using tools like CADD

• Post-translational modification detection:

  • Phospho-specific antibodies for phosphorylation sites

  • Ubiquitination analysis using anti-ubiquitin antibodies

  • Deglycosylation assays to identify glycosylation contributions

• Functional assays:

  • Site-directed mutagenesis to mimic identified variants

  • Phosphatase treatment to remove phosphorylations

  • Pulse-chase experiments to assess protein stability and processing

• Case study: p.Ala175Thr mutation:

  • This mutation reduces protein stability without affecting mRNA levels

  • Dimerization is impaired as shown by BN-PAGE

  • Normal subcellular localization but reduced peroxisomal abundance

  • CADD score correlates with disease severity and age of onset

What are the optimal preservation and extraction methods for maintaining HSD17B4 integrity in tissue samples?

For preserving HSD17B4 integrity:

• Tissue preservation protocols:

  • Flash freezing in liquid nitrogen is optimal for protein integrity

  • Formalin fixation should be limited to 24 hours to prevent epitope masking

  • For immunofluorescence, 4% paraformaldehyde fixation for 15-20 minutes preserves peroxisomal structure

• Protein extraction strategies:

  • Include protease inhibitors to prevent degradation

  • Use mild detergents (0.5% Triton X-100) to preserve protein complexes

  • For native analysis, avoid reducing agents that may disrupt disulfide bonds

• Subcellular fractionation:

  • Peroxisome isolation improves detection of low-abundance HSD17B4

  • Differential centrifugation or density gradient methods can be employed

  • Confirm fraction purity with peroxisomal markers like catalase or PMP70

• Buffer considerations:

  • For immunoprecipitation: PBS with 0.1% NP-40 and protease inhibitors

  • For dimerization studies: non-denaturing conditions without SDS

  • For Western blot: standard RIPA buffer with complete protease inhibitors

• Storage recommendations:

  • Store protein lysates at -80°C with glycerol (10%) to prevent freeze damage

  • Limit freeze-thaw cycles to maintain protein integrity

  • For long-term storage of antibodies, aliquot to avoid repeated thawing

How can researchers develop quantitative assays to measure HSD17B4 enzyme activity in correlation with protein levels?

For quantitative HSD17B4 enzyme activity assays:

• Activity measurement approaches:

  • Spectrophotometric assays monitoring NAD+/NADH conversion

  • Substrate conversion assays using radiolabeled or fluorescent substrates

  • Coupled enzyme assays to amplify detection sensitivity

• Domain-specific activity assessment:

  • Dehydrogenase activity: Measure oxidation of 3-hydroxyacyl-CoA to 3-ketoacyl-CoA

  • Hydratase activity: Assess conversion of 2-enoyl-CoA to 3-hydroxyacyl-CoA

  • Test both straight-chain and 2-methyl-branched-chain fatty acid substrates

• Correlation with protein levels:

  • Perform parallel Western blot analysis of the same samples

  • Calculate specific activity (activity/protein amount) to normalize data

  • Compare dimerization status (BN-PAGE) with enzymatic activity

• Patient-derived sample analysis:

  • Use fibroblasts from patients with different mutations

  • Correlate CADD scores with enzymatic activity and protein levels

  • Stratify by disease severity (infant-onset, juvenile-onset, adult-onset)

• Data interpretation considerations:

  • Distinguish between reduced expression and reduced specific activity

  • Consider post-translational modifications affecting activity

  • Account for dimerization defects versus catalytic site mutations

What controls are essential when evaluating HSD17B4 protein levels in disease state comparisons?

Essential controls for HSD17B4 disease state comparisons:

• Sample-type matched controls:

  • Age-matched control samples (particularly important for age-onset disorders)

  • Tissue-specific controls from the same anatomical region

  • Cell-type specific controls when using heterogeneous tissue samples

• Internal standardization controls:

  • General housekeeping proteins (β-actin, GAPDH) for loading normalization

  • Peroxisomal markers (PMP70, catalase) for compartment-specific normalization

  • Ratio analysis of HSD17B4 to peroxisomal proteins to detect specific changes

• Technical validation controls:

  • Multiple antibodies targeting different epitopes of HSD17B4

  • Recombinant HSD17B4 standards for quantitative comparisons

  • Gradient loading to ensure detection is in the linear range

• Disease-specific reference samples:

  • Known mutation carriers for comparative analysis

  • Samples representing different disease severities or progression stages

  • Related family members to account for genetic background effects

• Methodological controls:

  • For methylation studies: unmethylated and fully methylated controls

  • For protein analysis: untreated and protease-digested samples

  • For dimerization: heat-denatured samples to identify monomer position