ACA4 Antibody

What does ACA4 refer to in different research contexts?

ACA4 can refer to several distinct entities in scientific research:

• Carbonic Anhydrase IV (CA4): A membrane-bound isozyme of the carbonic anhydrase family detected at approximately 35 kDa in human lung tissue and specific cell lines .

• Anticardiolipin Antibody (ACA): An autoantibody targeting negatively charged phospholipids on platelets and endothelial cell membranes, commonly associated with autoimmune conditions .

• Atypical chemokine receptor 4 (ACKR4): A chemokine receptor-like molecule that does not couple to G protein signaling pathways, involved in regulating dendritic cell migration and tumor development .

• ACA4 Gene in Arabidopsis: Encodes a vacuolar membrane calcium-ATPase in plants with roles in osmotic stress response .

Researchers should clearly specify which ACA4 entity they are targeting to prevent confusion in scientific communications.

What are the key characteristics of ACA4 antibodies for research applications?

The characteristics vary significantly depending on the specific target:

• Anti-CA4 Antibodies: Typically recognize human Carbonic Anhydrase IV from Ala19-Lys283, with approximately 10% cross-reactivity with CA1, CA2, and mouse CA4, but not with CA3, 8, 9, 10, 12, 13, or 14 .

• Anti-ACKR4 Antibodies: Recently developed monoclonal antibodies (A4Mab-1, A4Mab-2, and A4Mab-3) detect mouse ACKR4 with dissociation constant (KD) values of 6.0 × 10^-9 M, 1.3 × 10^-8 M, and 1.7 × 10^-9 M, respectively .

• Anti-Anticardiolipin Antibodies: Primarily used in diagnostic applications for antiphospholipid syndrome, detected using ELISA methods with cardiolipin as antigen and β2-glycoprotein I (β2GPI) as an essential cofactor .

How are ACA4 antibodies validated for research applications?

Standard validation protocols include:

• Western Blotting: Confirming specific band detection at expected molecular weights (e.g., CA4 at ~35 kDa , ACKR4 at ~50 kDa ).

• Flow Cytometry: Verifying binding to cells expressing the target protein, as demonstrated with ACKR4-overexpressed CHO-K1 cells .

• Cross-reactivity Testing: Assessing specificity by testing against similar proteins from the same family .

• Peptide Blocking Experiments: Confirming specificity by showing that pre-incubation with target peptide blocks antibody binding, as demonstrated with A4Mab-1 and A4Mab-2 for ACKR4 .

• Positive/Negative Controls: Using tissues or cell lines known to express or lack the target protein (e.g., human lung tissue as positive control for CA4 ).

How do different ACA isotype levels correlate with systemic sclerosis progression?

Research has demonstrated significant correlations between antibody isotypes and disease progression in systemic sclerosis (SSc):

Values presented as median (interquartile range). This data demonstrates that higher antibody levels, particularly IgG and IgM isotypes, correlate with disease progression and organ involvement in systemic sclerosis .

What cross-reactivity considerations are critical when using ACA4 antibodies?

Cross-reactivity considerations depend on the specific ACA4 target and may significantly impact experimental interpretation:

• Anti-CA4 Antibodies: Exhibit approximately 10% cross-reactivity with recombinant human CA1, CA2, and recombinant mouse CA4, but do not cross-react with CA3, 8, 9, 10, 12, 13, or 14 . This requires careful interpretation when studying tissues expressing multiple CA isoforms.

• Anti-ACKR4 Antibodies: Specificity of newer antibodies like A4Mab-1, A4Mab-2, and A4Mab-3 has been validated through peptide blocking experiments, but researchers should verify specificity in their specific experimental systems .

• Anticardiolipin Antibodies: May cross-react with oxidized low-density lipoprotein, potentially contributing to foam cell formation and endothelial cell damage . This cross-reactivity has significant implications for understanding atherosclerosis pathogenesis in antiphospholipid syndrome.

How can researchers differentiate between specific and non-specific binding in ACA4 antibody assays?

To discriminate between specific and non-specific binding:

• Multiple Antibody Approach: Use different antibodies targeting distinct epitopes of the same protein to confirm results.

• Peptide Competition Assays: Pre-incubate antibody with the immunizing peptide to block specific binding, as demonstrated with A4Mab-1 and A4Mab-2 for ACKR4 .

• Negative Controls: Test the antibody in tissues or cells known not to express the target protein (e.g., LN229 cells without ACKR4 expression ).

• Knockout/Knockdown Controls: Use genetic approaches to reduce target protein expression and demonstrate corresponding loss of antibody binding.

• Optimized Blocking Conditions: Employ appropriate blocking agents and optimize buffer conditions to minimize non-specific interactions.

What are the optimal western blot protocols for detecting different ACA4 proteins?

For Carbonic Anhydrase IV/CA4 Detection:

• Sample Preparation: Use lysates from human lung tissue or Jurkat cell line.

• Electrophoresis Conditions: Non-reducing conditions with PVDF membrane.

• Antibody Concentration: 2 μg/mL of Anti-Human Carbonic Anhydrase IV/CA4 antibody.

• Secondary Antibody: HRP-conjugated Anti-Mouse IgG.

• Expected Band: ~35 kDa specific band.

• Buffer System: Immunoblot Buffer Group 1 .

For ACKR4 Detection:

• Sample Preparation: Cell lysates expressing ACKR4.

• Antibody Selection: A4Mab-1 and A4Mab-2 are effective, with A4Mab-2 showing superior reactivity (A4Mab-3 is ineffective for western blotting).

• Expected Band Size: ~50 kDa.

• Validation: Include peptide blocking controls to confirm specificity.

• Loading Control: β-actin is recommended .

How should flow cytometry protocols be optimized for ACA4 antibody detection?

For optimal flow cytometry detection:

• Antibody Selection: Verify flow cytometry compatibility, as not all western blot-validated antibodies work for flow cytometry. A4Mab-1, A4Mab-2, and A4Mab-3 all successfully detected mACKR4-overexpressed CHO-K1 cells by flow cytometry .

• Cell Preparation: Optimize fixation and permeabilization protocols based on target localization (membrane-bound versus intracellular).

• Antibody Titration: Determine optimal concentration through systematic titration experiments.

• Controls: Include fluorescence-minus-one (FMO), isotype, and positive/negative expression controls.

• Multi-parameter Design: Consider spectral overlap, fluorophore brightness, and compensation requirements.

• Binding Kinetics: Account for different antibody affinities (KD values of 6.0 × 10^-9 M, 1.3 × 10^-8 M, and 1.7 × 10^-9 M for A4Mab-1, A4Mab-2, and A4Mab-3, respectively) .

What controls are essential for reliable ACA4 antibody experiments?

Critical controls include:

• Positive Controls: Samples known to express the target (e.g., human lung tissue for CA4 , CHO/mACKR4 cells for ACKR4 ).

• Negative Controls: Samples lacking target expression (e.g., LN229 cells for ACKR4 ).

• Loading/Normalization Controls: Internal standards (e.g., β-actin) to normalize protein amounts .

• Isotype Controls: Matched isotype antibodies to assess non-specific binding.

• Peptide Competition Controls: Antibody pre-incubated with immunizing peptide to demonstrate specificity - essential for validating novel antibodies .

• Secondary Antibody-Only Controls: To assess background from secondary detection reagents.

• Dilution Series: To demonstrate dose-dependent binding characteristics.

How can researchers address inconsistent ACA4 antibody signals?

To troubleshoot inconsistent signals:

• Antibody Quality: Ensure antibody hasn't degraded; aliquot to avoid freeze-thaw cycles.

• Protocol Standardization: Systematically optimize antibody concentration, incubation time/temperature, and washing conditions.

• Sample Preparation: Maintain consistent lysis buffers, protease inhibitors, and protein extraction methods.

• Buffer Composition: Optimize blocking agents to reduce background and increase signal-to-noise ratio.

• Alternative Antibodies: Compare different antibodies targeting the same protein (e.g., A4Mab-1 vs A4Mab-2 for ACKR4, which showed different western blot sensitivity) .

• Exposure Parameters: Standardize image acquisition settings across experiments.

• Loading Consistency: Verify equal sample loading using appropriate controls.

What statistical approaches are appropriate for analyzing ACA4 antibody binding studies?

Recommended statistical methods include:

• Group Comparisons: Mann-Whitney U test for two independent groups and Kruskal-Wallis test with correction for multiple comparisons for more than two groups, as employed in systemic sclerosis ACA studies .

• Association Analysis: Binary logistic regression with adjustment for confounding variables (age, disease duration) to evaluate associations between antibody levels and disease status .

• Correlation Analysis: Spearman's rank correlation for non-parametric data when assessing relationships between antibody levels and clinical parameters.

• Survival Analysis: Kaplan-Meier curves and Cox proportional hazards models for time-to-event outcomes in longitudinal studies.

• Diagnostic Performance: Receiver operating characteristic (ROC) curve analysis to determine sensitivity, specificity, and optimal clinical cutoff values.

What is the role of ACA4 targets in disease pathogenesis?

The pathogenic roles vary by context:

• Anticardiolipin Antibodies (ACA): Play a critical role in antiphospholipid syndrome pathogenesis, contributing to thrombosis, thrombocytopenia, and spontaneous abortion . Mechanistically, ACA enhances monocyte chemotactic protein-1 (MCP-1) expression at both protein and mRNA levels, potentially contributing to atherosclerosis and inflammatory disease processes . ACA also induces nitric oxide production through increased inducible nitric oxide synthase expression, potentially impairing endothelium-derived nitric oxide function and increasing thrombosis risk .

• Anticentromere Antibodies (ACA): Associated with systemic sclerosis development and progression, with higher levels of IgG, IgM, and IgA isotypes correlating with transition from very early to definite systemic sclerosis and specific organ involvement patterns .

• Atypical Chemokine Receptor 4 (ACKR4): Regulates dendritic cell migration through chemokine gradient control and is implicated in tumor development in mouse models . Unlike conventional chemokine receptors, ACKR4 acts primarily through chemokine scavenging rather than direct signaling.

What emerging applications exist for ACA4 antibodies in research?

Cutting-edge applications include:

• Preclinical Model Development: Using newly developed tools like anti-ACKR4 antibodies (A4Mab-1, A4Mab-2, and A4Mab-3) to better understand chemokine regulation in mouse models of cancer and inflammation .

• Mechanistic Studies: Further elucidating how ACA contributes to pathology, particularly its role in enhancing MCP-1 expression and modulating nitric oxide production .

• Biomarker Development: Expanding ACA isotype profiling to predict disease progression and guide treatment decisions in systemic sclerosis, given the strong correlation between antibody levels and clinical outcomes .

• Chemokine Network Investigation: Using anti-ACKR4 antibodies to understand how atypical chemokine receptors regulate immune cell trafficking through gradient formation rather than direct signaling .

• Plant Stress Response Research: Investigating how ACA4 gene expression changes under osmotic stress conditions, with evidence showing expression maxima at specific NaCl concentrations (100 mM) .

How do ACA4 antibodies contribute to understanding signaling pathways?

ACA4 antibodies enable investigation of multiple signaling networks:

• Chemokine Signaling: Anti-ACKR4 antibodies help elucidate how atypical chemokine receptors regulate chemokine gradients through internalization and degradation rather than classical G-protein signaling .

• Nitric Oxide Pathway: Anticardiolipin antibodies induce nitric oxide production through increased expression of inducible nitric oxide synthase in both ex vivo and in vivo models, potentially creating feedback inhibition of endothelium-derived nitric oxide .

• Inflammatory Mediator Regulation: ACA enhances monocyte chemotactic protein-1 expression at both protein and mRNA levels, with implications for atherosclerosis and inflammatory disease pathogenesis .

• β2GPI-Dependent Pathways: Anticardiolipin antibodies from antiphospholipid syndrome patients require β2-glycoprotein I as a cofactor for cardiolipin binding, activating specific downstream signaling cascades .

• Calcium Homeostasis: In plant systems, antibodies against ACA4 gene products help study vacuolar membrane calcium-ATPase function in osmotic stress responses .