At2g33190 Antibody

What is the At2g33190 gene and its protein product?

At2g33190 encodes a putative F-box protein in Arabidopsis thaliana, also annotated as AtFDB16. It belongs to the F-box family of proteins containing a domain of unknown function (DUF295) . The protein has 379 amino acids and is categorized as a putative F-box protein that likely functions in protein-protein interactions and ubiquitin-mediated protein degradation pathways .

What types of antibodies are available for At2g33190 protein detection?

Several monoclonal antibody combinations are available for At2g33190 protein detection, typically targeting different regions of the protein:

• N-terminal antibodies (X-O49316-N): Target the N-terminus sequence

• C-terminal antibodies (X-O49316-C): Target the C-terminus sequence

• Middle region antibodies (X-O49316-M): Target non-terminus sequences

These antibodies are usually provided as combinations of individual monoclonal antibodies that recognize specific epitopes within these regions.

What are the typical applications for At2g33190 antibodies?

At2g33190 antibodies can be used in several experimental approaches:

• Western blotting (WB) for protein expression analysis

• Immunoprecipitation (IP) for protein-protein interaction studies

• Chromatin immunoprecipitation (ChIP) for DNA-protein interaction studies

• Immunocytochemistry/Immunofluorescence (ICC/IF) for cellular localization

The ELISA titer for these antibodies is typically around 10,000, corresponding to approximately 1 ng detection sensitivity on Western blots .

How should I validate the specificity of At2g33190 antibodies?

Validation should follow multiple steps:

• Genetic validation: Compare signal between wild-type and knockout/knockdown lines

• Peptide competition assay: Pre-incubate antibody with the immunizing peptide prior to use

• Cross-reactivity assessment: Test against related F-box proteins

• Expression correlation: Compare protein detection with known transcript levels

• Multiple antibody approach: Use antibodies targeting different regions of the same protein

Remember that approximately 50% of commercial antibodies may not meet basic standards for characterization, making validation particularly important .

What controls should I include when using At2g33190 antibodies?

For rigorous experimental design, include:

• Negative controls:

  • At2g33190 knockout/knockdown lines

  • Samples from non-plant organisms

  • Secondary antibody-only controls

  • Pre-immune serum controls

• Positive controls:

  • Recombinant At2g33190 protein

  • Arabidopsis samples with known At2g33190 overexpression

  • Tagged At2g33190 protein detected with tag-specific antibodies

• Loading controls:

  • Housekeeping proteins appropriate for your subcellular fraction

  • Total protein stains for normalization

How should I optimize Western blot conditions for At2g33190 antibodies?

Optimization should be systematic:

• Sample preparation:

  • Use 250 µl of plant extract for immunoprecipitation

  • Reserve 50 µl for Western blot analysis

  • Include protease inhibitors to prevent degradation

• Antibody dilution:

  • Test a range of concentrations

  • Start with manufacturer's recommendation (typically 1:500-1:2,000 for Western blot)

  • Report antibody concentration in protein terms rather than dilution factor for reproducibility

• Blocking conditions:

  • Test different blocking agents (BSA, milk, commercial blockers)

  • Optimize blocking time and temperature

• Detection methods:

  • Compare chemiluminescence, fluorescence, and chromogenic detection

  • Consider signal-to-noise ratio for each method

Why might I observe multiple bands on Western blots with At2g33190 antibodies?

Multiple bands could result from:

• Post-translational modifications: F-box proteins often undergo phosphorylation, ubiquitination, or SUMOylation

• Protein degradation: Sample preparation issues leading to protein breakdown

• Splice variants: Alternative splicing producing different protein isoforms

• Cross-reactivity: Antibody recognizing related F-box proteins

• Non-specific binding: Particularly common with polyclonal antibodies

To address this, validate the specificity using knockout lines and peptide competition assays, and consider using antibodies targeting different regions of the protein to confirm the identity of specific bands .

What steps should I take if At2g33190 antibody shows weak or no signal?

Follow this systematic approach:

• Antibody validation:

  • Confirm antibody activity using peptide ELISA

  • Test different antibody batches or sources

• Protein extraction optimization:

  • Try different extraction buffers

  • Ensure protein is not denatured in a way that destroys the epitope

  • Check protein transfer efficiency

• Signal enhancement strategies:

  • Increase antibody concentration or incubation time

  • Use more sensitive detection methods

  • Try protein enrichment through immunoprecipitation before detection

  • Consider signal amplification systems

• Expression verification:

  • Verify expression of At2g33190 at the transcript level

  • Consider if the protein is expressed at very low levels naturally

How can I address high background issues with At2g33190 antibodies?

To reduce background:

• Blocking optimization:

  • Test different blocking agents (BSA, milk, commercial blockers)

  • Extend blocking time

  • Add blocking agent to antibody dilution buffer

• Washing optimization:

  • Increase wash duration and frequency

  • Try different detergent concentrations (Tween-20, NP-40)

• Antibody dilution:

  • Use higher dilutions of primary and secondary antibodies

  • Pre-absorb antibodies with plant extracts from knockout lines

• Sample preparation:

  • Ensure thorough removal of cellular debris

  • Consider additional purification steps

How can At2g33190 antibodies be used in protein-protein interaction studies?

For studying At2g33190 protein interactions:

• Co-immunoprecipitation (Co-IP):

  • Use 250 µl of extract and 5 µl of antibodies for immunoprecipitation

  • Include appropriate controls (IgG, knockout lines)

  • Use crosslinking agents to capture transient interactions

  • Verify interactions with reciprocal Co-IP

• Proximity ligation assay (PLA):

  • Combine At2g33190 antibody with antibodies against potential interaction partners

  • Allows visualization of interactions in situ with subcellular resolution

• Chromatin immunoprecipitation (ChIP):

  • For F-box proteins involved in transcriptional regulation

  • Follow standard ChIP protocols with At2g33190 antibodies

  • Validate with sequential ChIP (re-ChIP) approaches

How can I use At2g33190 antibodies to study post-translational modifications?

For PTM analysis:

• Modification-specific detection:

  • Run samples on Phos-tag gels to separate phosphorylated forms

  • Use 2D gel electrophoresis to separate by charge and mass

  • Perform immunoprecipitation followed by mass spectrometry

• Treatment comparisons:

  • Compare samples treated with phosphatase inhibitors vs. phosphatases

  • Analyze samples from plants under different stress conditions

  • Compare wild-type vs. mutants in PTM pathways

• Sequential immunoprecipitation:

  • First IP with At2g33190 antibody

  • Second IP with PTM-specific antibodies (phospho, ubiquitin, SUMO)

What approaches can be used to study At2g33190 localization in different tissues and developmental stages?

For localization studies:

• Immunohistochemistry protocols:

  • Fixation optimization for plant tissues (paraformaldehyde, glutaraldehyde)

  • Permeabilization methods compatible with plant cell walls

  • Antigen retrieval techniques if needed

• Co-localization studies:

  • Use with organelle markers for subcellular localization

  • Combine with in situ hybridization for simultaneous protein/transcript detection

• Developmental analysis:

  • Sample different tissues and developmental stages

  • Compare with transcript expression patterns

  • Correlate with known developmental markers

How do antibodies against At2g33190 compare with antibodies targeting other F-box proteins?

Comparative considerations:

• Cross-reactivity potential:

  • F-box domain conservation may lead to cross-recognition

  • Validate specificity against related F-box proteins

  • Choose antibodies targeting unique regions outside the F-box domain

• Application differences:

  • Some F-box protein antibodies may work better in certain applications

  • Compare performance in Western blot vs. immunoprecipitation vs. immunofluorescence

• Reference data:

  • Compare your results with published data on similar F-box proteins

  • Use data from F-box protein databases to validate expected results

How can At2g33190 antibody data be integrated with other omics approaches?

Integration strategies:

• Proteomics correlation:

  • Compare antibody-based quantification with mass spectrometry data

  • Validate protein-protein interactions identified by IP-MS with direct antibody detection

• Transcriptomic integration:

  • Correlate protein levels (antibody detection) with transcript levels (RNA-seq)

  • Identify post-transcriptional regulation by comparing protein/RNA ratios

• Phenotypic correlation:

  • Link protein expression/localization patterns with phenotypic data

  • Compare with data from knockout/overexpression lines

What are the key considerations when interpreting contradictory results between different At2g33190 antibodies?

When facing conflicting results:

• Epitope differences:

  • Antibodies targeting different regions may give different results

  • Some epitopes may be masked by protein-protein interactions

  • Post-translational modifications may affect epitope recognition

• Methodological validation:

  • Perform side-by-side comparisons using identical samples

  • Test both antibodies in knockout/knockdown lines

  • Consider if different fixation/extraction methods affect epitope availability

• Confirmatory approaches:

  • Use orthogonal methods (e.g., tagged protein expression)

  • Perform rescue experiments in knockout backgrounds

  • Consider mass spectrometry validation of protein identity

How can deep learning approaches enhance At2g33190 antibody specificity prediction?

Computational approaches:

• Sequence-based prediction:

  • Deep learning models can be trained to distinguish between antibodies with different specificities

  • Models can analyze complementarity-determining regions (CDRs) for specificity prediction

  • This approach has been successful with SARS-CoV-2 and influenza antibodies

• Epitope mapping:

  • Computational prediction of antibody binding sites

  • In silico modeling of antibody-antigen interactions

  • Validation of predictions with experimental epitope mapping

• Cross-reactivity assessment:

  • Algorithms to predict potential cross-reactive proteins

  • Integration with proteome databases for specificity scoring

What are the latest methodological advances in At2g33190 and other plant protein antibody validation?

Recent advances include:

• High-throughput validation approaches:

  • Simultaneous testing against multiple related proteins

  • Microarray-based validation against proteome fragments

  • CRISPR knockout cell line panels for specificity testing

• Standardization initiatives:

  • Research Identification Initiative (RRID) for antibody tracking

  • Independent validation by organizations like YCharOS

  • Journals requiring specific validation data for antibody-based studies

• Alternative binding reagents:

  • Recombinant antibodies with defined sequences

  • Nanobodies and other single-domain antibodies

  • Aptamers as alternative detection reagents

What information should be included in publications when reporting At2g33190 antibody experiments?

Essential reporting elements:

• Antibody details:

  • Vendor and catalog number

  • Research Resource Identifier (RRID)

  • Clone names for monoclonal antibodies

  • Host species and antibody type (monoclonal/polyclonal)

  • Target region (N-terminal, C-terminal, middle region)

• Experimental conditions:

  • Antibody concentration (preferably in µg/ml rather than dilution)

  • Incubation conditions (time, temperature, buffer)

  • Blocking reagents and conditions

  • Detection methods and sensitivity

• Validation evidence:

  • Controls used (positive, negative, loading)

  • Validation methods employed

  • Full blot images including molecular weight markers

How can I ensure reproducibility when using different batches of At2g33190 antibodies?

Batch consistency approaches:

• Internal reference standards:

  • Maintain a reference sample set for testing new batches

  • Document batch-to-batch variation systematically

  • Consider creating a standard curve with recombinant protein

• Lot testing protocol:

  • Test each new lot against previous lots

  • Document minimum required concentration for detection

  • Establish acceptance criteria for new batches

• Long-term strategy:

  • Consider recombinant antibodies with defined sequences

  • Archive working antibody aliquots for critical projects

  • Document all experimental conditions meticulously

What are the best practices for long-term storage and handling of At2g33190 antibodies?

Optimal handling procedures:

• Storage conditions:

  • Follow manufacturer recommendations (typically -20°C)

  • Avoid repeated freeze-thaw cycles

  • Consider adding preservatives for working dilutions (0.01% sodium azide)

• Aliquoting strategy:

  • Create single-use aliquots upon receipt

  • Document date and freeze-thaw cycle number

  • Store in non-frost-free freezers if possible

• Quality control:

  • Periodically test activity against reference samples

  • Include positive controls in each experiment

  • Document lot numbers and their performance