FCER1A Antibody, FITC conjugated

What is FCER1A and why is it important in immunological research?

FCER1A (Fc epsilon RI alpha) is the alpha subunit of the high-affinity receptor for the Fc region of immunoglobulin E (IgE). This receptor plays a crucial role in initiating allergic responses and is involved in immunity against certain parasitic infections. FCER1A binds to the Fc region of IgE with high affinity, and when allergens cross-link the bound IgE, it triggers cell activation, leading to the release of inflammatory mediators .

The receptor is primarily expressed on mast cells and basophils, making it a key molecular target for studying allergic diseases and developing therapeutic interventions. Recent research has also uncovered regulatory mechanisms involving natural antisense transcripts that control FCER1A expression, adding another layer of complexity to its biology .

What are the different types of FCER1A antibodies available and their specific characteristics?

There are two main types of FCER1A antibodies available for research:

• Polyclonal antibodies: These are derived from multiple B cell lineages and recognize multiple epitopes on the FCER1A antigen. For example, the rabbit polyclonal antibody against FCER1A (CSB-PA008532LC01HU) is conjugated to FITC and targets human FCER1A. It uses recombinant human High affinity immunoglobulin epsilon receptor subunit alpha protein (amino acids 26-205) as the immunogen .

• Monoclonal antibodies: These are produced from a single B cell clone and recognize a single epitope. The Armenian Hamster monoclonal antibody (FITC-65091) targets mouse FCER1A and is applicable for flow cytometry applications .

How does FITC conjugation enhance the utility of FCER1A antibodies?

FITC (Fluorescein isothiocyanate) conjugation provides several advantages for research applications:

• Direct detection: FITC conjugation allows direct visualization of the antibody binding without requiring secondary detection reagents, simplifying experimental protocols and reducing potential sources of variability .

• Compatibility with standard equipment: FITC has excitation/emission maxima wavelengths of approximately 495 nm / 524 nm, making it compatible with standard flow cytometers and fluorescence microscopes available in most research facilities .

• Multiplexing capabilities: FITC can be combined with other fluorophores that have distinct spectral properties for multicolor analyses, enabling simultaneous detection of multiple markers on the same cell population.

• Quantitative analysis: The fluorescence intensity correlates with the amount of bound antibody, allowing quantitative assessment of FCER1A expression levels on cell surfaces.

What are the validated applications for FCER1A antibodies?

FCER1A antibodies have been validated for several research applications, depending on the specific product:

The rabbit polyclonal FCER1A antibody (CSB-PA008532LC01HU) has been validated for:

• ELISA (Enzyme-Linked Immunosorbent Assay) for protein detection and quantification

• Dot Blot assays for rapid qualitative analysis

The Armenian Hamster monoclonal FCER1A antibody (FITC-65091) has been specifically validated for:

• Flow cytometry applications, particularly with mouse MC/9 cells, which are known to express FCER1A

Additional applications that may be suitable but require validation include:

• Immunohistochemistry/Immunofluorescence for tissue localization studies

• Immunoprecipitation for protein-protein interaction studies

• Western blotting for protein expression analysis

What is the recommended protocol for flow cytometric analysis using FCER1A antibody?

For optimal flow cytometric analysis with FCER1A antibody, FITC conjugated:

• Sample preparation:

  • Isolate cells of interest (e.g., basophils, mast cells, or cell lines like MC/9)

  • Wash cells 2-3 times with cold PBS containing 1-2% BSA or FBS

  • Adjust cell concentration to approximately 1×10^6 cells/100 μL

• Staining procedure:

  • Add the FITC-conjugated FCER1A antibody at the appropriate dilution (sample-dependent, requires titration)

  • Incubate for 30 minutes at 4°C in the dark

  • Wash cells 2-3 times with staining buffer

  • Resuspend in suitable buffer for analysis

• Controls (essential for accurate analysis):

  • Unstained cells to establish baseline autofluorescence

  • Isotype control (e.g., Armenian Hamster IgG-FITC for FITC-65091)

  • Known positive samples (e.g., MC/9 cells for mouse FCER1A)

• Instrument settings:

  • Optimize flow cytometer settings for FITC detection (excitation: 495 nm, emission: 524 nm)

  • Perform compensation if using multiple fluorophores

  • Collect sufficient events for statistical significance (minimum 10,000 events)

The antibody dilution should be empirically determined for each experimental system to obtain optimal results. For the FITC-65091 antibody, it is specifically recommended to titrate in each testing system .

How should FCER1A antibodies be stored and handled to maintain optimal performance?

Proper storage and handling are critical for maintaining antibody integrity and performance:

For rabbit polyclonal FCER1A antibody (CSB-PA008532LC01HU):

• Store at -20°C or -80°C upon receipt

• Avoid repeated freeze-thaw cycles, which can degrade the antibody and reduce its efficacy

• The antibody is provided in a buffer containing 50% glycerol, 0.01M PBS, pH 7.4, and 0.03% Proclin 300 as preservative

For Armenian Hamster monoclonal antibody (FITC-65091):

• Store at 2-8°C (refrigeration)

• Avoid exposure to light, as FITC is light-sensitive and can photobleach

• Stable for one year after shipment when stored properly

• Provided in PBS buffer with 0.09% sodium azide

General handling recommendations:

• Aliquot antibodies upon receipt to minimize freeze-thaw cycles

• Use aseptic technique when handling to prevent contamination

• Allow frozen antibodies to thaw completely at room temperature before use

• Centrifuge briefly before opening vials to collect all material

• Return to recommended storage conditions immediately after use

How should researchers validate FCER1A antibody specificity for their experimental system?

Comprehensive validation of antibody specificity is crucial for reliable research outcomes:

• Positive and negative controls:

  • Test the antibody on cell types known to express FCER1A (positive controls)

  • For mouse studies, MC/9 cells serve as excellent positive controls

  • Test on cell types known not to express FCER1A (negative controls)

• Genetic approaches:

  • Use FCER1A knockout or knockdown cells as negative controls

  • Compare staining in wild-type versus FCER1A deficient samples

• Blocking experiments:

  • Pre-incubate the antibody with recombinant FCER1A protein

  • This should block specific binding and reduce staining intensity

• Multiple detection methods:

  • Confirm expression using alternative techniques (qPCR, Western blot)

  • Use multiple antibody clones targeting different epitopes

• Cross-reactivity assessment:

  • Test on closely related proteins to ensure specificity

  • Check for unexpected binding patterns in tissues or cells

Validation is especially important when examining complex biological systems where FCER1A expression may be regulated by factors such as FCER1A-AS (antisense transcript) .

What experimental approaches can be used to study the relationship between FCER1A and its natural antisense transcript?

Recent research has revealed the importance of FCER1A-AS (natural antisense transcript) in controlling FCER1A expression. To investigate this relationship:

• Co-expression analysis:

  • Perform strand-specific RT-PCR to simultaneously detect both sense (FCER1A-S) and antisense (FCER1A-AS) transcripts

  • Analyze co-expression patterns in different cell types and under various conditions

  • IL-3-induced FcεRIα-expressing cells and MC/9 cell line are suitable models

• Targeted knockdown approaches:

  • Use CRISPR/RfxCas13d (CasRx) to selectively knock down FCER1A-AS

  • Assess effects on FCER1A-S mRNA and protein expression

  • Flow cytometry with FITC-conjugated FCER1A antibody can quantify protein expression changes

• In vivo models:

  • Generate or utilize FCER1A-AS-deficient mice

  • Compare phenotypes with FCER1A knockout mice

  • Evaluate responses in models such as Schistosoma japonicum infection and IgE-mediated cutaneous anaphylaxis

• Mechanism studies:

  • Investigate the molecular mechanisms by which FCER1A-AS regulates FCER1A-S

  • Analyze cis-regulatory effects on transcription or post-transcriptional regulation

  • Perform RNA-protein interaction studies to identify potential mediators

Research has demonstrated that FCER1A-AS deficiency leads to markedly decreased expression of FCER1A-S mRNA and proteins, suggesting a positive regulatory role of the antisense transcript .

How can researchers optimize antibody concentration for different experimental applications?

Determining the optimal antibody concentration is critical for obtaining reliable and reproducible results:

• Titration approach:

  • Prepare serial dilutions of the antibody (e.g., 1:10, 1:50, 1:100, 1:500)

  • Test each dilution on appropriate positive control samples

  • Analyze signal-to-background ratio at each concentration

  • Select the concentration that provides maximum specific signal with minimal background

• Application-specific considerations:

  • Flow cytometry: Titrate on cells with known FCER1A expression (e.g., MC/9 cells for mouse studies)

  • ELISA: Generate standard curves with various antibody concentrations against known antigen amounts

  • Dot Blot: Test serial dilutions against both positive and negative control proteins

• Sample-specific adjustments:

  • Different sample types may require different antibody concentrations

  • Primary cells may require different concentrations than cell lines

  • Tissue samples may need higher concentrations due to increased background

• Batch testing:

  • Each new lot of antibody should be tested alongside previous lots

  • Document optimal concentrations for each application to ensure reproducibility

For the FITC-65091 antibody, the manufacturer specifically recommends titration in each testing system to obtain optimal results, highlighting the importance of this step .

What are common challenges in FCER1A detection and how can they be addressed?

Researchers may encounter several challenges when working with FCER1A antibodies:

• Low signal intensity:

  • Cause: Insufficient antibody concentration, low FCER1A expression, or degraded antibody

  • Solution: Increase antibody concentration, use fresh antibody, verify storage conditions, and confirm FCER1A expression in your samples

• High background:

  • Cause: Non-specific binding, insufficient washing, autofluorescence

  • Solution: Increase washing steps, use appropriate blocking reagents, include dead cell discrimination dyes, adjust instrument settings

• Inconsistent results:

  • Cause: Variability in staining protocol, cell preparation, or antibody quality

  • Solution: Standardize protocols, prepare fresh cells, use aliquoted antibodies to avoid freeze-thaw cycles

• False negatives:

  • Cause: Downregulation of FCER1A expression, deficiency in FCER1A-AS

  • Solution: Verify expression using alternative methods, check for FCER1A-AS expression

  • Research has shown that deficiency in FCER1A-AS leads to reduced FCER1A expression

• Cross-reactivity:

  • Cause: Antibody binding to similar proteins

  • Solution: Use more specific antibodies, include appropriate controls, validate with genetic approaches

• Photobleaching:

  • Cause: FITC sensitivity to light exposure

  • Solution: Minimize exposure to light during preparation and storage, consider using more photostable fluorophores for long-term imaging

How should flow cytometry data for FCER1A expression be analyzed and interpreted?

Proper analysis of flow cytometry data ensures accurate interpretation of FCER1A expression:

• Gating strategy:

  • Use forward/side scatter to exclude debris and select cells of interest

  • Apply dead cell exclusion if using a viability dye

  • For basophils or mast cells, use additional markers to identify the population of interest

• Control-based analysis:

  • Use unstained and isotype controls to set negative population boundaries

  • Positive controls (e.g., MC/9 cells for mouse FCER1A) help confirm proper staining

• Expression metrics:

  • Percentage of FCER1A-positive cells within the population

  • Mean or median fluorescence intensity (MFI) to quantify expression level

  • Consider both metrics for complete understanding of expression patterns

• Comparative analysis:

  • For experimental treatments, calculate fold changes in expression relative to controls

  • Use appropriate statistical tests to determine significance of differences

  • Consider biological relevance of observed changes

• Multiparameter analysis:

  • When using multiple markers, analyze co-expression patterns

  • Consider dimensionality reduction techniques for complex datasets

  • Correlate FCER1A expression with functional parameters or other markers

• Visualization:

  • Use appropriate plots (histograms, dot plots) to display data

  • Include statistics and gating information on plots

  • Present raw data alongside processed results for transparency

What advanced analytical approaches can be applied to FCER1A expression studies?

For more sophisticated analysis of FCER1A expression:

• Single-cell analysis:

  • Combine flow cytometry with single-cell RNA sequencing

  • Correlate protein expression (by FCER1A antibody) with transcriptomic profiles

  • Identify heterogeneity within FCER1A-expressing populations

• Functional correlation:

  • Integrate FCER1A expression data with functional assays

  • Analyze relationship between receptor expression and degranulation, cytokine production, or allergic responses

  • Study effects of FCER1A-AS expression on receptor function and downstream signaling

• Computational modeling:

  • Develop predictive models of FCER1A expression based on various factors

  • Simulate effects of interventions targeting FCER1A or FCER1A-AS

  • Integrate multi-omics data for comprehensive understanding

• Longitudinal studies:

  • Track FCER1A expression over time in disease progression or treatment

  • Use consistent protocols and antibody lots for reliable comparisons

  • Normalize to stable reference markers to account for technical variation

• Systems biology approaches:

  • Map FCER1A into broader signaling networks

  • Analyze co-expression patterns with other receptors and signaling molecules

  • Study regulatory networks including FCER1A-AS and other non-coding RNAs

How can FCER1A antibodies contribute to studying allergic disorders and parasitic infections?

FCER1A antibodies offer powerful tools for investigating mechanisms and potential therapies:

• Disease mechanism studies:

  • Quantify FCER1A expression levels in patients versus healthy controls

  • Track expression changes during disease progression or treatment

  • Study receptor modulation upon allergen exposure or during parasitic infections

• Cellular characterization:

  • Identify and isolate FCER1A-expressing cells from clinical samples

  • Compare receptor densities across different patient populations

  • Characterize phenotypic and functional subsets of mast cells and basophils

• Therapeutic development:

  • Screen compounds that modulate FCER1A expression or function

  • Monitor receptor internalization or downregulation upon treatment

  • Evaluate effects of targeting FCER1A-AS on allergic responses

• Animal models:

  • Compare FCER1A expression and function in wild-type versus disease models

  • Assess receptor dynamics during experimental allergic responses

  • Evaluate phenotypes of FCER1A-AS deficient mice in parasitic infection models like Schistosoma japonicum and in IgE-mediated cutaneous anaphylaxis

• Biomarker development:

  • Evaluate FCER1A expression as a potential diagnostic or prognostic marker

  • Correlate expression levels with disease severity or treatment response

  • Develop standardized flow cytometry panels for clinical applications

What insights does the discovery of FCER1A-AS provide for allergy research?

The discovery of FCER1A-AS (natural antisense transcript) offers new perspectives on FCER1A regulation:

• Novel regulatory mechanism:

  • FCER1A-AS is co-expressed with FCER1A-S in both IL-3-induced FcεRIα-expressing cells and in the MC/9 cell line

  • Selective knockdown of FCER1A-AS using CRISPR/RfxCas13d leads to markedly decreased expression of both FCER1A-S mRNA and proteins

  • FCER1A-AS deficiency is associated with lack of FCER1A-S expression in vivo

• Therapeutic implications:

  • Targeting FCER1A-AS could provide new approaches for modulating allergic responses

  • Homozygous mice deficient in FCER1A-AS show similar phenotypes to FCER1A knockout mice in Schistosoma japonicum infection and in IgE-FcεRIα-mediated cutaneous anaphylaxis

  • This suggests potential for developing antisense-based therapeutics

• Evolutionary considerations:

  • The conservation of this regulatory mechanism across species suggests important biological functions

  • Understanding species differences in FCER1A/FCER1A-AS regulation may explain variability in allergic responses

• Transcriptional regulation:

  • The co-expression pattern of sense/antisense transcripts appears critical for successful FcεRIα expression in vivo

  • This represents a novel pathway for the control of FcεRIα expression and consequently IgE-mediated allergic responses

• Broader implications:

  • This discovery highlights the importance of investigating non-coding RNAs in immune regulation

  • Similar mechanisms may operate for other key immunoreceptors

How can researchers integrate FCER1A studies with broader immunological research?

FCER1A research can be integrated into wider immunological studies: