The A1BG antibody targets alpha-1B-glycoprotein (A1BG), a 68–80 kDa monomeric plasma glycoprotein belonging to the immunoglobulin superfamily . Structurally, A1BG contains five V-type Ig-like domains and is expressed primarily by hepatocytes in response to growth hormone . Its mature form spans 474 amino acids (aa 22–495) and includes five intrachain disulfide bonds .
CRISP3 Interaction: A1BG binds CRISP3, a cysteine-rich secretory protein, to regulate its availability. This interaction may modulate sperm survival during fertilization by blocking uterine neutrophil responses .
Cancer Biomarker Potential: A1BG expression correlates with disease progression in breast, liver, and other cancers, suggesting its utility in diagnostics .
Nutrient Transport: A1BG facilitates fatty acid and cholesterol transport, aiding metabolic homeostasis .
A1BG antibodies are critical in studying:
Drug Resistance: A1BG-AS1 lncRNA (a paralog) regulates ABCB1 (P-glycoprotein), linked to multidrug resistance in breast cancer .
Immune Modulation: A1BG may influence cell adhesion and immune cell migration, impacting tissue repair and inflammation .
The following research findings highlight the potential roles and implications of A1BG in various biological processes:
A1BG (Alpha-1-B glycoprotein) is a plasma protein with a molecular mass of approximately 63 kDa that is predominantly expressed in the liver. Despite being known for decades, its precise biological function remains somewhat elusive. A1BG belongs to the immunoglobulin superfamily, containing five repeating structural domains of about 92-98 amino acids each, which show sequence similarity to the variable regions of immunoglobulins .
Research significance stems from A1BG's identification as an autoantigen in rheumatoid arthritis and its overexpression in various cancers, including pancreatic ductal adenocarcinoma, bladder, breast, and lung cancer. It has also been observed at elevated levels in pediatric patients with steroid-resistant nephrotic syndrome and liver cancer cell lines, suggesting its potential as a cancer-associated biomarker .
Several types of A1BG antibodies are available for research purposes, including:
Rabbit polyclonal antibodies (such as ab231784) suitable for Western blot (WB) and immunohistochemistry with paraffin-embedded tissues (IHC-P), reactive with both mouse and human samples .
Mouse monoclonal antibodies (such as clone 4B5, MA5-15616) that target A1BG in indirect ELISA, IHC, and WB applications, specifically reactive with human samples .
Custom polyclonal antibodies (such as CAB11583) designed for Western blot applications with high reactivity to human samples .
These antibodies recognize different epitopes and may have varying specificities depending on the immunogen used and production methods.
Validating antibody specificity is crucial for ensuring reliable experimental results. For A1BG antibodies, researchers typically employ multiple approaches:
Western blot analysis: Testing the antibody against predicted molecular weight targets (approximately 54 kDa for A1BG) in various samples such as human/mouse serum, liver tissue lysates, or cancer cell lines like MCF7 (human breast adenocarcinoma cells) .
Recombinant protein testing: Confirming antibody reactivity against purified recombinant A1BG protein to verify target recognition .
Immunohistochemistry: Examining tissue-specific expression patterns, such as in formalin-fixed, paraffin-embedded liver tissues, which should show characteristic A1BG staining patterns .
Positive and negative controls: Including samples known to express (liver tissues) or lack A1BG to confirm specific binding.
Cross-reactivity assessment: Testing reactivity against related proteins to ensure the antibody doesn't recognize unintended targets.
For optimal Western blot results with A1BG antibodies, researchers should consider the following protocol elements:
Sample preparation: Process tissue lysates (especially liver) or serum samples with appropriate lysis buffers containing protease inhibitors.
Protein loading: Load 20-30 μg of total protein per lane for cell/tissue lysates or dilute serum samples appropriately.
Antibody concentration: Use primary antibody at approximately 2 μg/mL concentration, as demonstrated with ab231784 for optimal results .
Expected band size: Look for bands at approximately 54 kDa, which is the predicted molecular weight for A1BG, though post-translational modifications may result in apparent size variations .
Controls: Include recombinant A1BG protein as a positive control when available, and consider using mouse liver tissue lysate or human MCF7 cell lysate as demonstrated in validation studies .
Detection systems: Compatible with standard HRP-conjugated secondary antibodies and ECL detection systems.
Optimization: Temperature, incubation time, and blocking conditions may need optimization depending on the specific antibody clone and sample type.
For successful immunohistochemistry with A1BG antibodies:
Sample preparation: Use formalin-fixed, paraffin-embedded tissues sectioned at 4-6 μm thickness.
Antigen retrieval: Heat-mediated antigen retrieval in citrate buffer (pH 6.0) is typically effective for A1BG antibodies.
Antibody concentration: For example, ab231784 has been validated at 20 μg/ml concentration for IHC-P applications on mouse liver tissue .
Detection system: DAB (3,3'-diaminobenzidine) staining provides good visualization of A1BG expression, particularly in liver tissues .
Incubation conditions: Typically overnight incubation at 4°C yields optimal results.
Controls: Include liver tissues as positive controls since A1BG is prominently expressed there.
Counterstaining: Hematoxylin counterstaining allows visualization of tissue architecture and cellular localization of A1BG.
When investigating RNA-protein interactions involving A1BG-AS1 (the antisense RNA related to A1BG), researchers should consider these methodological points:
Probe design: Synthesize biotin-labeled antisense and sense RNA for A1BG-AS1, ensuring full coverage of potential protein binding regions .
Protein partner selection: Consider testing interaction with RNA binding proteins like IGF2BP2, which has been identified as interacting with A1BG-AS1 in breast cancer cells .
Experimental conditions: Culture biotin-labeled RNAs with streptavidin beads and cell lysates for approximately 2 hours, followed by centrifugation at 4°C for 5 minutes as demonstrated in published protocols .
Washing steps: Thoroughly wash the RNA-protein complex to remove non-specific binding.
Detection methods: Use Western blot with antibodies against potential binding partners (such as IGF2BP2) to confirm interactions .
Controls: Include sense RNA as negative control and known RNA-protein interactions as positive controls.
Validation: Confirm findings with complementary methods such as RNA immunoprecipitation (RIP) assays .
A1BG has been implicated in several cancer types, and antibodies against this protein can help elucidate its mechanisms:
Expression profiling: Use A1BG antibodies in tissue microarrays to evaluate expression patterns across cancer types and correlate with clinical outcomes. This is particularly relevant for pancreatic, bladder, breast, and lung cancers where A1BG overexpression has been documented .
Cell line studies: Employ Western blot and immunofluorescence with A1BG antibodies to compare expression levels between normal and cancer cell lines, such as MCF7 breast cancer cells .
Functional studies: After A1BG knockdown or overexpression, use antibodies to confirm protein modulation before assessing phenotypic changes.
Interaction studies: Investigate binding partners of A1BG in cancer contexts, particularly CRISP family proteins, using co-immunoprecipitation with A1BG antibodies .
In vivo models: Apply A1BG antibodies in xenograft models to assess how expression correlates with tumor growth, metastasis, and therapy resistance.
Biomarker validation: Evaluate A1BG's potential as a diagnostic or prognostic biomarker by analyzing expression in patient samples using immunohistochemistry or ELISA with validated antibodies.
Recent research has identified interactions between A1BG and cysteine-rich secretory proteins (CRISPs), especially CRISP-3. To study these interactions:
Co-immunoprecipitation: Use A1BG antibodies to pull down protein complexes from biological samples, followed by Western blot with CRISP-specific antibodies to detect interaction .
Recombinant protein studies: Express recombinant A1BG and CRISP proteins to study direct interactions in vitro, using A1BG antibodies for detection and quantification.
Domain mapping: Express individual Ig domains of A1BG (particularly the third Ig repeat domain which has been implicated in sterol binding inhibition) and test their interaction with CRISP proteins using antibodies for detection .
Functional assays: Assess how A1BG affects CRISP protein functions, such as sterol-binding and export capabilities, using appropriate in vitro and cellular assays .
Structural studies: Use antibodies as tools in protein purification workflows for subsequent structural analysis of A1BG-CRISP complexes.
Competitive binding assays: Investigate whether different CRISP family members compete for binding to A1BG, using antibodies to quantify bound proteins.
Recent studies have identified connections between A1BG-AS1 (the antisense RNA) and adriamycin resistance in breast cancer. While this involves the RNA rather than the protein directly, understanding potential connections requires:
Expression correlation: Use A1BG antibodies alongside RNA detection methods to determine if protein levels correlate with A1BG-AS1 expression in resistant versus sensitive cell lines (e.g., MCF-7/ADR vs. MCF-7) .
Mechanistic pathways: Investigate whether A1BG protein interacts with components of the IGF2BP2-ABCB1 axis that was identified in A1BG-AS1-mediated resistance .
Functional studies: After modulating A1BG protein levels (through overexpression or knockdown), assess changes in adriamycin sensitivity using cell viability assays.
Co-localization studies: Use immunofluorescence with A1BG antibodies and RNA FISH for A1BG-AS1 to determine if and where the protein and antisense RNA co-localize in resistant cells .
Clinical correlation: Apply A1BG antibodies in IHC studies of patient samples to evaluate whether protein expression correlates with treatment response and resistance development.
Researchers may encounter several challenges when working with A1BG antibodies:
Background signal: High background in Western blots or IHC may occur. Optimize by:
Increasing blocking time/concentration (5% BSA or milk)
Reducing primary antibody concentration
Adding 0.1-0.3% Triton X-100 to wash buffers
Increasing wash duration and frequency
Multiple bands in Western blot: A1BG may undergo post-translational modifications or processing. Address by:
Weak or absent signal:
Optimize antigen retrieval for IHC (try different buffers and incubation times)
Increase antibody concentration incrementally
Extend primary antibody incubation time
Use signal enhancement systems
Cross-reactivity: Some antibodies may recognize related proteins. Minimize by:
Selecting highly-specific antibody clones
Validating with knockout/knockdown controls
Performing peptide competition assays
Batch-to-batch variation: Address by:
Standardizing protocols with each new antibody lot
Maintaining reference samples for comparability
Requesting validation data for each lot from suppliers
Different tissues may require specific optimization strategies:
Liver tissue (high A1BG expression):
Use lower antibody concentrations (10-15 μg/ml) to prevent oversaturation
Shorter primary antibody incubation time
Mild antigen retrieval conditions
Cancer tissues (variable expression):
Titrate antibody concentration based on expected expression levels
Include positive control tissues (liver) on the same slide
Consider dual staining with cancer markers to correlate expression
Non-expressing tissues (negative controls):
Use these to establish background staining levels
Help differentiate specific from non-specific staining
Tissue-specific optimization parameters:
Fixation duration may affect epitope availability
Antigen retrieval methods (heat vs. enzymatic)
Blocking reagents (BSA vs. serum vs. commercial blockers)
Incubation temperature (4°C overnight vs. room temperature)
Automated vs. manual staining:
Automated systems may require different antibody dilutions
Protocol transfer between methods requires validation
When discovering new functions for A1BG, thorough validation is essential:
Multiple antibody validation:
Confirm findings using at least two different antibody clones targeting distinct A1BG epitopes
Compare monoclonal and polyclonal antibody results
Genetic manipulation:
Perform knockdown/knockout experiments using siRNA, shRNA, or CRISPR
Conduct rescue experiments with wild-type and mutant A1BG constructs
Use antibodies to verify knockdown/overexpression efficiency
Cross-species validation:
Complementary techniques:
Support antibody-based findings with non-antibody methods (mass spectrometry, RNA expression)
Confirm protein-protein interactions with multiple methods (co-IP, proximity ligation, FRET)
Functional relevance:
Connect molecular findings to cellular phenotypes
Validate in vivo significance in appropriate animal models
Correlate with clinical observations when possible
Recent findings suggest A1BG inhibits sterol-binding and export functions of CAP proteins . Antibodies can facilitate further investigation:
Domain-specific studies: Generate and utilize antibodies against specific Ig domains of A1BG, particularly the third Ig repeat domain identified as important for sterol binding inhibition .
Cellular localization: Use immunofluorescence with A1BG antibodies to track localization relative to sterol transport machinery in various cell types.
Co-localization studies: Perform dual staining with A1BG antibodies and markers of sterol trafficking pathways to identify sites of functional interaction.
Proximity labeling: Couple A1BG antibodies with proximity labeling techniques to identify novel interaction partners in sterol metabolism pathways.
Quantitative analysis: Employ A1BG antibodies in ELISA or other quantitative assays to measure how A1BG levels correlate with cellular sterol content under various conditions.
In vivo metabolic studies: Use antibodies to track A1BG expression in response to metabolic challenges or in models of dysregulated sterol metabolism.
To evaluate A1BG's potential as a biomarker, researchers could:
Tissue microarray analysis: Use validated A1BG antibodies to screen large cohorts of patient samples across different cancer types and stages, correlating expression with clinical outcomes .
Liquid biopsy development: Develop and validate sensitive ELISA assays using A1BG antibodies to detect circulating A1BG in patient serum or plasma.
Multiplex biomarker panels: Incorporate A1BG antibodies into multiplex detection systems alongside other established biomarkers to improve diagnostic accuracy.
Post-translational modification analysis: Use modified-specific antibodies to determine if particular A1BG variants have enhanced diagnostic value.
Longitudinal studies: Apply antibody-based detection methods to monitor A1BG levels during disease progression and treatment response.
Comparative analysis: Evaluate A1BG alongside current gold-standard biomarkers to determine added diagnostic or prognostic value.
The relationship between A1BG protein and its antisense RNA (A1BG-AS1) represents an intriguing research direction:
Co-expression analysis: Use A1BG antibodies alongside RNA detection methods to determine if protein and antisense RNA levels correlate across different tissues and disease states .
Regulatory studies: Manipulate A1BG-AS1 expression and assess impacts on A1BG protein levels using antibody-based quantification methods.
Mechanistic investigation: Determine whether A1BG-AS1 acts in cis to regulate A1BG expression or functions independently through trans mechanisms.
Cellular localization: Employ immunofluorescence with A1BG antibodies combined with RNA FISH for A1BG-AS1 to examine spatial relationships within cells .
Clinical correlation: Analyze patient samples for both A1BG protein (via antibody-based methods) and A1BG-AS1 RNA levels, correlating with disease features like adriamycin resistance in breast cancer .
Functional consequences: After modulating either A1BG or A1BG-AS1, use various assays to determine if they influence similar or distinct cellular pathways.