si:ch211-214c7.5 Antibody

What is si:ch211-214c7.5 and why is it significant for research?

si:ch211-214c7.5 is a protein-coding gene located on chromosome 1 in zebrafish (Danio rerio). Its significance stems from being orthologous to human C19orf67 (chromosome 19 open reading frame 67), providing a model system for studying this protein's function across species . The protein belongs to the DUF3314 family (Domain of Unknown Function), indicating its biological role remains to be fully characterized . Research on this protein may contribute to understanding conserved functions between zebrafish and humans, particularly since orthologous proteins often maintain similar biological roles across evolutionary distance.

What are the basic properties of si:ch211-214c7.5 protein?

si:ch211-214c7.5 encodes a protein of 344 amino acids in length, as documented in UniProtKB (A3KNM4) . The protein contains a domain of unknown function (DUF3314), suggesting it belongs to a protein family whose biological activity remains to be characterized . Multiple transcript variants have been identified, including si:ch211-214c7.5-201 (1,870 nt), si:ch211-214c7.5-202 (1,110 nt), and si:ch211-214c7.5-203 (608 nt) . These different splice variants may perform distinct biological functions or display tissue-specific expression patterns, though this requires further investigation.

What types of antibodies are available for si:ch211-214c7.5 research?

Several types of antibodies against si:ch211-214c7.5 are commercially available for research purposes:

Researchers should note that antibodies targeting the human ortholog C19orf67 are also available, such as polyclonal antibodies targeting amino acids 76-125 of human C19orf67, which may be useful for comparative studies .

How should researchers validate si:ch211-214c7.5 antibody specificity?

Validating antibody specificity for si:ch211-214c7.5 requires a multi-faceted approach:

• Positive and negative controls: Include tissue samples from wild-type zebrafish alongside genetic knockdown/knockout models of si:ch211-214c7.5.

• Peptide competition assay: Pre-incubate the antibody with excess purified si:ch211-214c7.5 peptide before application in your experiment. Signal reduction indicates specificity.

• Cross-reactivity assessment: Test the antibody against recombinant si:ch211-214c7.5 protein alongside related proteins to ensure minimal cross-reactivity.

• Orthogonal detection methods: Correlate antibody detection with mRNA expression using techniques like qPCR or RNA-seq.

• Multiple antibody concordance: Compare results using different antibodies targeting distinct epitopes of si:ch211-214c7.5.

Since si:ch211-214c7.5 is orthologous to human C19orf67, researchers should be particularly careful about potential cross-reactivity when working with samples containing both zebrafish and human proteins .

What are the optimal conditions for Western blotting with si:ch211-214c7.5 antibodies?

When performing Western blotting with si:ch211-214c7.5 antibodies, researchers should consider the following optimized protocol:

• Sample preparation: Extract proteins using a buffer containing protease inhibitors to prevent degradation.

• Gel selection: Use 10-12% SDS-PAGE gels for optimal separation of the 344 amino acid protein.

• Transfer parameters: Transfer to PVDF membranes at 100V for 1 hour in Tris-glycine buffer with 20% methanol.

• Blocking conditions: Block with 5% non-fat dry milk in TBST (Tris-buffered saline with 0.1% Tween-20) for 1 hour at room temperature.

• Primary antibody dilution: Start with a 1:1000 dilution of the antibody in blocking buffer, though optimal working dilution should be determined empirically for each application .

• Incubation conditions: Incubate with primary antibody overnight at 4°C with gentle agitation.

• Detection system: Use an appropriate HRP-conjugated secondary antibody and ECL detection system.

Note that the expected molecular weight of si:ch211-214c7.5 should be confirmed based on its amino acid sequence, with attention to potential post-translational modifications that may affect migration patterns.

How can si:ch211-214c7.5 antibodies be used in comparative studies with human C19orf67?

For comparative studies between zebrafish si:ch211-214c7.5 and human C19orf67:

• Co-immunoprecipitation studies: Use species-specific antibodies to identify conserved interaction partners across species, providing insight into functional conservation.

• Tissue expression profiling: Compare expression patterns in homologous tissues between zebrafish and humans using immunohistochemistry to identify conserved expression domains.

• Subcellular localization: Determine if both proteins share similar subcellular localization using immunofluorescence microscopy, indicating potential functional conservation.

• CRISPR-Cas9 phenotypic rescue: Assess functional conservation by determining if human C19orf67 can rescue phenotypes in si:ch211-214c7.5 knockout zebrafish.

• Structural analysis: Use antibodies to purify both proteins for comparative structural studies using techniques like circular dichroism or X-ray crystallography.

Researchers studying human C19orf67 should note that antibodies specifically targeting the human ortholog are available, such as those recognizing amino acids 76-125 , enabling direct comparison with zebrafish studies.

What approaches can be used to study the unknown function of si:ch211-214c7.5 using antibodies?

To elucidate the function of this protein with unknown function (DUF3314 family) :

• Immunoprecipitation coupled with mass spectrometry: Identify protein interaction partners that may provide clues to function.

• Chromatin immunoprecipitation (ChIP): Determine if the protein associates with chromatin, suggesting a role in transcriptional regulation.

• Proximity labeling techniques: Use antibody-guided BioID or APEX2 proximity labeling to identify the protein's immediate microenvironment.

• Subcellular fractionation with immunoblotting: Determine the protein's subcellular localization across different cellular states.

• Developmental immunohistochemistry: Map expression across developmental stages to identify temporal patterns suggesting functional roles.

• Stress response studies: Examine changes in expression or localization under various cellular stresses using antibody-based detection methods.

• Post-translational modification mapping: Use phospho-specific or other modification-specific antibodies to characterize regulatory mechanisms.

A multi-omics approach combining antibody-based techniques with genomic and proteomic methods will likely yield the most comprehensive understanding of this protein's function.

How should researchers address potential cross-reactivity with other proteins in the DUF3314 family?

Cross-reactivity with other proteins containing the DUF3314 domain presents a significant challenge for antibody specificity. Researchers should:

• Perform epitope mapping: Identify the exact epitope recognized by the antibody and compare it to sequences of other DUF3314-containing proteins.

• Pre-adsorption controls: Pre-adsorb antibodies with recombinant proteins containing similar DUF3314 domains to remove cross-reactive antibodies.

• Parallel knockout controls: Include samples from si:ch211-214c7.5 knockout organisms alongside wild-type samples in all experiments.

• Epitope-specific antibody generation: Consider developing antibodies against unique regions outside the conserved DUF3314 domain.

• Western blot analysis of multiple tissues: Compare banding patterns across tissues with known expression profiles to identify potential cross-reactive bands.

• Validation in heterologous expression systems: Test antibody specificity against tagged versions of si:ch211-214c7.5 and related proteins expressed in cell culture.

For researchers working with human samples, it's worth noting that antibodies specific to human C19orf67 may have been validated against a synthetic peptide located between amino acids 76-125, which may offer higher specificity .

What are the key considerations for immunohistochemistry with si:ch211-214c7.5 antibodies in zebrafish tissues?

When performing immunohistochemistry with si:ch211-214c7.5 antibodies:

• Fixation optimization: Compare multiple fixation methods (4% PFA, Bouin's, etc.) to determine optimal epitope preservation.

• Antigen retrieval: Test various antigen retrieval methods (heat-induced in citrate buffer, enzymatic treatment, etc.) to maximize signal.

• Developmental stage selection: Consider that expression may vary dramatically across developmental stages; use RNA expression data to guide tissue selection.

• Permeabilization protocol: Optimize detergent concentration and incubation time, especially important for whole-mount zebrafish embryo staining.

• Signal amplification: Consider tyramide signal amplification for detecting low-abundance proteins.

• Autofluorescence management: Use Sudan Black B treatment or spectral unmixing to reduce zebrafish-specific autofluorescence.

• Multichannel imaging: Include co-staining with established cell-type markers to identify expressing cell populations.

Given the current lack of extensive characterization, researchers should correlate protein expression patterns with available mRNA data for si:ch211-214c7.5 to validate antibody specificity in tissue contexts .

How should researchers quantify and analyze si:ch211-214c7.5 expression data from antibody-based studies?

For robust quantification of si:ch211-214c7.5 expression:

• Western blot densitometry: Normalize band intensity to loading controls (β-actin, GAPDH) using software like ImageJ, ensuring signals fall within the linear range of detection.

• Immunohistochemistry quantification: Use automated image analysis software with consistent thresholding parameters across samples. Consider:

  • Cell counting approaches for nuclear or cytoplasmic signals

  • Pixel intensity measurements for diffuse signals

  • Colocalization coefficients when performing double-labeling experiments

• Flow cytometry analysis: When using fluorescently-labeled antibodies, establish appropriate gating strategies based on negative controls.

• Statistical considerations:

  • Use appropriate statistical tests based on data distribution

  • Account for biological and technical replicates

  • Consider power analysis to determine adequate sample sizes

• Standardization: Include calibration samples with known protein concentrations to enable inter-experimental comparisons.

Given the limited characterization of si:ch211-214c7.5, researchers should present their quantitative data alongside appropriate controls and validation experiments to ensure accurate interpretation.

What approaches should be used to analyze contradictory findings between si:ch211-214c7.5 antibody results and gene expression data?

When faced with discrepancies between antibody detection and gene expression data:

• Methodological validation:

  • Confirm antibody specificity using knockout/knockdown controls

  • Verify qPCR primer specificity and efficiency

  • Assess potential cross-reactivity with related proteins

• Biological explanations:

  • Investigate post-transcriptional regulation mechanisms (miRNAs, RNA-binding proteins)

  • Examine protein stability and turnover rates

  • Consider developmental timing differences between mRNA and protein expression

  • Evaluate potential splice variant-specific expression patterns across the three known transcript variants

• Integrative analysis:

  • Perform temporal studies to determine if mRNA peaks precede protein peaks

  • Use subcellular fractionation to check if proteins are sequestered in specific compartments

  • Consider post-translational modifications that might affect antibody binding

• Technical troubleshooting:

  • Evaluate fixation artifacts in immunohistochemistry

  • Check for potential interference from sample preparation methods

  • Assess detergent compatibility with the target epitope

A combined approach using multiple antibodies targeting different epitopes, alongside orthogonal techniques like RNA-seq and mass spectrometry, can help resolve contradictory findings and lead to a more accurate understanding of si:ch211-214c7.5 biology.

How can machine learning and active learning approaches enhance antibody-antigen binding prediction for si:ch211-214c7.5 studies?

Recent advances in computational methods offer promising approaches for si:ch211-214c7.5 antibody research:

• Library-on-library screening optimization: Machine learning models can predict antibody-antigen binding by analyzing many-to-many relationships between antibodies and antigens, potentially reducing experimental costs for si:ch211-214c7.5 binding studies .

• Active learning strategies: Novel active learning approaches can iteratively expand labeled datasets, improving out-of-distribution prediction performance. Recent research demonstrated that:

  • The best algorithms reduced required antigen mutant variants by up to 35%

  • Learning process acceleration of up to 28 steps compared to random baselines was achieved

  • Three of fourteen tested algorithms significantly outperformed random data labeling approaches

• Computational epitope mapping: Machine learning methods can predict antibody binding epitopes on si:ch211-214c7.5, guiding more rational antibody development.

• Cross-species binding prediction: Computational approaches can help predict whether antibodies against human C19orf67 might recognize zebrafish si:ch211-214c7.5 and vice versa.

• Affinity optimization: Computational design can guide antibody engineering to improve specificity and affinity for challenging targets like proteins with unknown function.

These computational approaches could significantly accelerate research on proteins of unknown function like si:ch211-214c7.5 by reducing the experimental burden while improving specificity and cross-reactivity prediction.

What are the future prospects for CRISPR-based genome editing combined with antibody detection for si:ch211-214c7.5 functional studies?

The integration of CRISPR technology with antibody-based detection offers powerful approaches for si:ch211-214c7.5 functional characterization:

• CRISPR knockout validation: Generate precise si:ch211-214c7.5 knockout zebrafish lines using available gRNA vectors to validate antibody specificity and establish loss-of-function phenotypes .

• Epitope tagging: Use CRISPR knock-in strategies to add epitope tags to the endogenous si:ch211-214c7.5 gene, enabling detection with highly specific commercial tag antibodies.

• Protein domain dissection: Create targeted deletions of specific domains (like the DUF3314 domain) to assess their contribution to protein function and antibody binding.

• Ortholog replacement: Swap zebrafish si:ch211-214c7.5 with human C19orf67 to assess functional conservation using species-specific antibodies.

• Conditional regulation systems: Combine CRISPR with degron tags or other conditional systems to enable temporal control of protein expression, with antibody-based detection for validation.

• Single-cell functional genomics: Integrate CRISPR screening with antibody-based single-cell proteomics to identify functional pathways and interactions.

These approaches provide a comprehensive toolkit for functional characterization of understudied proteins like si:ch211-214c7.5, particularly valuable given its unknown function and potential relevance to human biology through its ortholog C19orf67.