ZNHIT2 Antibody

What is ZNHIT2 and what biological functions does it serve?

ZNHIT2 belongs to a family of HIT-finger proteins characterized by the presence of a HIT domain, a roughly 50-residue zinc-binding domain containing conserved cysteine (Cys) and histidine (His) residues . Functionally, ZNHIT2 acts as a bridging factor mediating the interaction between the R2TP/Prefoldin-like (R2TP/PFDL) complex and U5 small nuclear ribonucleoprotein (U5 snRNP) . It is required for the interaction of R2TP complex subunit RPAP3 and prefoldin-like subunit URI1 with U5 snRNP proteins EFTUD2 and PRPF8 . ZNHIT2 may also play a role in regulating the composition of the U5 snRNP complex . Tissue distribution analysis shows that ZNHIT2 is highly expressed in testis . Alternative names include C11orf5, Zinc finger HIT domain-containing protein 2, and Protein FON .

What types of ZNHIT2 antibodies are commercially available for research?

Several types of ZNHIT2 antibodies are available, varying in host species, clonality, and applications:

These antibodies target different regions of ZNHIT2, which can be important depending on your experimental needs and whether specific domains are involved in interactions of interest .

What are the optimal experimental applications for ZNHIT2 antibodies?

ZNHIT2 antibodies have been validated for multiple applications, each with specific recommended protocols:

For Western Blot applications, ZNHIT2 has been successfully detected in multiple sample types including HeLa cells, human brain tissue, mouse brain tissue, and K-562 cells .

What is the expected molecular weight of ZNHIT2 and how does this impact antibody selection?

ZNHIT2 has a calculated molecular weight of 43 kDa (403 amino acids), but is typically observed at 45-50 kDa on Western blots . This discrepancy between calculated and observed molecular weight is important to consider when evaluating antibody specificity. The difference may be attributed to post-translational modifications, protein folding effects, or potentially splice variants. When selecting antibodies, researchers should confirm that the product documentation acknowledges this size discrepancy and provides validation data showing detection at the expected observed molecular weight range .

How should ZNHIT2 antibodies be stored to maintain optimal performance?

Proper storage is crucial for maintaining antibody activity. Based on product specifications:

General storage recommendations include:

• Avoiding repeated freeze-thaw cycles

• Storing in small aliquots if using frequently

• Keeping away from light (especially for conjugated antibodies)

• Following manufacturer's specific guidance for each product

How can I effectively validate the specificity of a ZNHIT2 antibody for my research?

Rigorous validation of ZNHIT2 antibodies is essential for reliable research outcomes. Consider implementing these complementary validation strategies:

• Genetic knockdown/knockout verification: Utilize siRNA knockdown of ZNHIT2 (as demonstrated in published research) to confirm decreased signal in your detection system . This approach provides strong evidence of antibody specificity.

• Multiple epitope approach: Compare detection patterns using antibodies targeting different regions of ZNHIT2 (e.g., ab254950 targeting aa 150-300 versus ab126133 targeting aa 1-250) .

• Recombinant expression controls: Use overexpression systems with tagged ZNHIT2 as positive controls alongside endogenous detection.

• Orthogonal detection methods: Complement antibody-based detection with mRNA analysis (RT-qPCR or in situ hybridization) to confirm expression patterns match.

• Mass spectrometry validation: Verify immunoprecipitated proteins by mass spectrometry to confirm ZNHIT2 identity.

• Tissue/cell type expression profiling: Compare antibody detection across tissues with known ZNHIT2 expression patterns (e.g., high expression in testis as noted in the literature) .

Remember that validation should be specific to each experimental application, as antibody performance may vary between techniques.

What methodologies are most effective for studying ZNHIT2's role in protein complex formation?

ZNHIT2 functions as a bridging factor between the R2TP/PFDL complex and U5 snRNP. These interaction studies require specialized approaches:

• Co-Immunoprecipitation (CoIP): Published research has successfully used CoIP with FLAG-tagged R2TP/PFDL components (RPAP3, URI1) to detect interactions with U5 snRNP proteins (EFTUD2, PRPF8), with ZNHIT2 mediating this interaction . This approach can be combined with ZNHIT2 knockdown to assess bridging function.

• Tandem Affinity Purification coupled with Mass Spectrometry (TAP-MS): Reciprocal TAP-MS experiments with ZNHIT2 have revealed substantial amounts of both R2TP/PFDL complex and U5 snRNP components, confirming its role in complex formation .

• Proximity-dependent Biotin Identification (BioID-MS): This technique provides complementary information to affinity purification approaches by identifying proteins in close proximity to ZNHIT2 in living cells .

• Domain mapping experiments: Creating deletion mutants of ZNHIT2, particularly focusing on the zinc finger HIT domain, can help determine which regions are essential for interactions with specific complex components.

• Crosslinking coupled with immunoprecipitation: Chemical crosslinking before cell lysis can stabilize transient interactions, potentially capturing more complete complexes.

Each approach has strengths and limitations; combining multiple methods provides the most comprehensive understanding of ZNHIT2's role in complex formation .

How can I optimize experimental conditions for detecting ZNHIT2-R2TP/PFDL-U5 snRNP interactions?

Detecting ZNHIT2's bridging function between complexes requires careful optimization:

• Lysis condition optimization: Use gentle lysis buffers that preserve complex integrity. Consider:

  • Low ionic strength buffers with physiological pH

  • Mild non-ionic detergents at low concentrations (0.1-0.5% NP-40 or Triton X-100)

  • Protease and phosphatase inhibitor cocktails

  • Brief sonication or other gentle disruption methods

• Antibody selection strategy: Choose antibodies that don't target interaction domains. The zinc finger HIT domain mediates interaction with RUVBL2 , so antibodies targeting other regions might be preferable for immunoprecipitation studies.

• ZNHIT2 knockdown controls: As demonstrated in published work, ZNHIT2 knockdown significantly reduces the association of R2TP/PFDL with U5 snRNP components. This approach provides a valuable negative control to validate observed interactions .

• Sequential immunoprecipitation: First immunoprecipitate with anti-ZNHIT2, then elute and re-immunoprecipitate with antibodies against complex components to verify direct interactions versus indirect associations.

• Nuclease treatment: Consider treating lysates with nucleases to determine if interactions are RNA-dependent, which is particularly relevant for snRNP complexes.

These optimizations should be systematically tested and documented to establish reproducible protocols for studying ZNHIT2-mediated complex interactions.

What factors should I consider when interpreting ZNHIT2 detection in microscopy-based applications?

When using ZNHIT2 antibodies for immunofluorescence or immunohistochemistry, consider these interpretative factors:

• Subcellular localization expectations: ZNHIT2's role in R2TP/PFDL and U5 snRNP interactions suggests primarily nuclear localization, with potential enrichment in nuclear speckles where splicing factors concentrate. Any unexpected localization patterns should be carefully validated.

• Fixation method impacts: Paraformaldehyde fixation has been successfully used with ab126133 at 1/500 dilution in HeLa cells . Different fixation methods may affect epitope accessibility:

  • Paraformaldehyde: Preserves morphology but may mask some epitopes

  • Methanol/acetone: May better preserve certain epitopes but can distort morphology

  • Combined approaches: Consider PFA fixation followed by methanol permeabilization

• Signal validation strategies:

  • Co-staining with markers of known ZNHIT2-interacting complexes (U5 snRNP components)

  • Comparison with ZNHIT2-GFP fusion protein localization

  • siRNA knockdown control to confirm signal specificity

  • Z-stack imaging to confirm true colocalization versus superimposition

• Background versus specific signal: Carefully titrate antibody concentration and optimize blocking conditions. For IHC-P applications, a 1:50 dilution of ab254950 has been reported effective for human bone marrow tissue , but optimal concentration may vary by tissue type and fixation method.

• Detection system considerations: Fluorophore selection should account for tissue autofluorescence; enzymatic detection methods may require additional optimization steps.

Comprehensive controls and systematic optimization will yield the most reliable microscopy results with ZNHIT2 antibodies.

What advanced statistical approaches can be used to analyze ZNHIT2 antibody-based quantitative data?

When generating quantitative data using ZNHIT2 antibodies (western blot densitometry, immunofluorescence intensity, etc.), sophisticated analytical approaches include:

• Normalization strategies:

  • For western blots: Normalize ZNHIT2 signal to validated housekeeping proteins

  • For immunofluorescence: Use nuclear area or total protein stains for normalization

  • Consider multiple normalization methods and compare results for robustness

• Variance component analysis: Determine sources of variability in ZNHIT2 detection:

  • Biological replication (different samples)

  • Technical replication (same sample, multiple measurements)

  • Antibody lot variability

  • Experimental day effects

• Dose-response modeling: For treatments affecting ZNHIT2 expression/localization:

  • Fit appropriate mathematical models (linear, sigmoidal, etc.)

  • Calculate EC50 or other relevant parameters

  • Compare model parameters across conditions

• Machine learning approaches: For complex image analysis:

  • Supervised classification of ZNHIT2 localization patterns

  • Feature extraction to characterize staining patterns

  • Correlation with biological outcomes

• Bayesian inference: Incorporate prior knowledge about ZNHIT2 expression:

  • Use tissue-specific expression data to inform analysis

  • Update probability estimates as new data is collected

  • Account for measurement uncertainty

Why might Western blot detection of ZNHIT2 show unexpected band patterns?

Western blot inconsistencies with ZNHIT2 detection can stem from several factors:

• Molecular weight considerations: ZNHIT2 has a calculated molecular weight of 43 kDa but is typically observed at 45-50 kDa . This difference likely reflects post-translational modifications. Additional unexpected bands may indicate:

  • Proteolytic degradation (add fresh protease inhibitors)

  • Splice variants (verify with RT-PCR)

  • Post-translational modifications (phosphorylation, ubiquitination)

  • Non-specific antibody binding (optimize blocking and antibody dilution)

• Sample preparation optimization:

  • Ensure complete protein denaturation (adequate SDS, boiling time)

  • Use fresh samples or proper preservation methods

  • Consider specialized lysis buffers for nuclear proteins

  • Test multiple extraction protocols if nuclear extraction is challenging

• Antibody-specific considerations:

  • Titrate antibody concentration (recommended range for 16885-1-AP is 1:500-1:2000)

  • Compare multiple ZNHIT2 antibodies targeting different epitopes

  • Test blocking optimization (BSA vs. milk, concentration, time)

  • Include peptide competition controls for polyclonal antibodies

• Positive control selection: Use samples known to express ZNHIT2, such as:

  • HeLa cells

  • Human brain tissue

  • Mouse brain tissue

  • K-562 cells

Systematic optimization and thorough controls will help establish reliable ZNHIT2 western blot protocols.

How can I minimize background and maximize signal specificity in ZNHIT2 immunostaining?

Optimizing signal-to-noise ratio in ZNHIT2 immunostaining requires attention to multiple parameters:

• Antibody selection and titration:

  • Start with manufacturer's recommended dilution (e.g., 1:50 for IHC-P with ab254950 , 1:500 for ICC/IF with ab126133 )

  • Perform systematic titration experiments (typically 2-fold dilution series)

  • Compare polyclonal versus monoclonal antibodies if both are available

• Blocking optimization:

  • Test different blocking agents (BSA, normal serum, commercial blockers)

  • Optimize blocking time (1 hour to overnight)

  • Consider adding low concentrations of detergents to blocking solution

  • Test pre-incubation with isotype control immunoglobulins

• Antigen retrieval methods:

  • Compare heat-induced epitope retrieval methods (citrate vs. EDTA buffers)

  • Optimize retrieval time, temperature, and pH

  • Consider enzyme-based retrieval alternatives

  • Test no retrieval as baseline

• Detection system selection:

  • Compare direct vs. amplified detection methods

  • Optimize enzyme substrate development time for chromogenic detection

  • Select fluorophores with minimal spectral overlap with tissue autofluorescence

  • Consider signal amplification systems for low-abundance targets

• Control implementation:

  • Include no-primary-antibody controls

  • Use isotype controls at matching concentration

  • Include ZNHIT2-low and ZNHIT2-high tissues in the same experiment

  • Consider ZNHIT2 knockdown controls when possible

Systematic documentation of optimization experiments will facilitate reproducible protocols for specific applications.

What strategies can resolve detection issues when studying ZNHIT2 in complex experimental systems?

When encountering difficulties detecting ZNHIT2 in complex systems like tissue samples or specialized cell types:

• Alternative antibody approaches:

  • Try antibodies targeting different ZNHIT2 epitopes

  • Test both monoclonal and polyclonal antibodies

  • Consider directly conjugated primary antibodies to eliminate secondary antibody issues

  • Try recombinant antibody technology products for improved consistency

• Sample preparation refinements:

  • Optimize protein extraction for nuclear proteins

  • Consider subcellular fractionation to enrich for ZNHIT2-containing compartments

  • Implement immunoprecipitation before detection for enrichment

  • Test specialized fixation protocols for difficult tissues

• Alternative detection technologies:

  • Proximity ligation assay (PLA) for detecting ZNHIT2 interactions

  • Mass spectrometry-based targeted proteomics

  • RNA-based approaches (in situ hybridization, RT-PCR)

  • CRISPR-based tagging of endogenous ZNHIT2

• Functional assays as proxies:

  • Measure functions of ZNHIT2-dependent complexes

  • Assess U5 snRNP assembly or activity

  • Analyze splicing efficiency as downstream readout

  • R2TP/PFDL complex interaction assays

• Heterologous expression systems:

  • Express tagged versions of ZNHIT2

  • Utilize inducible expression systems

  • Consider domain-specific constructs to map interactions

These alternative approaches can provide complementary data when direct detection of endogenous ZNHIT2 proves challenging.

How can I design experiments to specifically study ZNHIT2's bridging function between protein complexes?

To investigate ZNHIT2's role as a molecular bridge between R2TP/PFDL and U5 snRNP:

• Knockdown-rescue experimental design:

  • Deplete endogenous ZNHIT2 using siRNA or CRISPR

  • Rescue with wild-type or domain-mutant ZNHIT2 constructs

  • Assess complex formation by co-immunoprecipitation

  • Analyze functional consequences (splicing efficiency, etc.)

• Structure-function analysis:

  • Create deletion mutants removing specific ZNHIT2 domains

  • Point mutations in the zinc finger HIT domain

  • Chimeric constructs with domains from related proteins

  • Test each variant's ability to bridge complex formation

• Proximity labeling approaches:

  • Fuse ZNHIT2 to BioID, TurboID, or APEX2

  • Perform proximity labeling experiments

  • Compare biotinylated protein profiles in wild-type vs. domain mutants

  • Identify differential labeling of R2TP/PFDL vs. U5 snRNP components

• Live-cell imaging strategies:

  • Create fluorescent protein fusions with ZNHIT2 and complex components

  • Perform fluorescence recovery after photobleaching (FRAP)

  • Use fluorescence resonance energy transfer (FRET) to measure direct interactions

  • Implement fluorescence correlation spectroscopy (FCS) for dynamic measurements

• In vitro reconstitution:

  • Express and purify recombinant ZNHIT2 and interaction partners

  • Perform in vitro binding assays with purified components

  • Use biophysical techniques (ITC, SPR) to measure binding parameters

  • Attempt reconstitution of minimal functional complexes

Published research has demonstrated that ZNHIT2 knockdown significantly reduces the association of R2TP/PFDL components (RPAP3, URI1) with U5 snRNP proteins (EFTUD2, PRPF8), providing strong evidence for its bridging function .

What are the most recent methodological advances for studying ZNHIT2 in research contexts?

Recent technological advances applicable to ZNHIT2 research include:

• Antibody engineering approaches:

  • Recombinant antibody technology has produced monoclonal ZNHIT2 antibodies with improved batch-to-batch consistency

  • Antibody pairs optimized for multiplex detection systems allow simultaneous measurement of ZNHIT2 with interaction partners

  • Conjugation-ready formats facilitate custom labeling for specialized applications

• CRISPR-based technologies:

  • CUT&Tag for precise chromatin profiling if ZNHIT2 has chromatin association

  • CRISPR activation/inhibition for controlled ZNHIT2 expression modulation

  • Base editing for introducing specific mutations to functional domains

  • Endogenous tagging strategies for visualization and purification

• Advanced proteomic approaches:

  • Crosslinking mass spectrometry to map protein interaction interfaces

  • Hydrogen-deuterium exchange mass spectrometry to study conformational changes

  • Thermal proteome profiling to identify ZNHIT2-dependent complexes

  • Single-cell proteomics to assess ZNHIT2 expression heterogeneity

• Computational modeling:

  • AlphaFold2 and RoseTTAFold for structural prediction of ZNHIT2 and complexes

  • Molecular dynamics simulations to study domain interactions

  • Network analysis approaches to position ZNHIT2 in broader interaction networks

  • Machine learning classification of HIT domain protein functions

• Spatial biology methods:

  • Spatial transcriptomics to map ZNHIT2 expression in tissue context

  • Super-resolution microscopy for detailed localization studies

  • Multiplexed ion beam imaging for simultaneous detection of multiple proteins

  • Live-cell single-molecule tracking to study ZNHIT2 dynamics

These advancing technologies open new avenues for investigating ZNHIT2's functions in increasingly sophisticated experimental paradigms.