At5g49610 Antibody

What is the At5g49610 F-box protein and why is it significant for plant research?

The At5g49610 is an F-box protein first identified in Arabidopsis thaliana that has homologs across multiple plant species including Nicotiana tabacum (common tobacco) and Oryza sativa (rice) . F-box proteins function as components of SCF (Skp1, Cullin, F-box) ubiquitin ligase complexes, playing crucial roles in targeted protein degradation through the ubiquitin-proteasome pathway. The At5g49610 protein is significant for plant research because it participates in cellular processes including hormone signaling, development, and stress responses. Multiple isoforms have been identified, including isoform X1 and X2 in tobacco, suggesting differential expression or function depending on developmental stage or environmental conditions .

What are the common applications for At5g49610 antibodies in plant science?

At5g49610 antibodies are primarily used in applications that require protein detection and localization in plant tissues. Common applications include:

These applications allow researchers to investigate protein expression levels, tissue distribution, subcellular localization, and protein-protein interactions involving At5g49610 .

How should I validate the specificity of an At5g49610 antibody before experimental use?

Proper validation of At5g49610 antibodies requires multiple complementary approaches:

• Western blot validation: Test the antibody against:

  • Wild-type plant tissue

  • Knockout/knockdown lines (if available)

  • Tissues with known expression levels

  • Recombinant At5g49610 protein as a positive control

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide before application to confirm binding specificity.

• Multiple detection methods: Confirm results using different techniques (e.g., western blot, immunofluorescence, and immunoprecipitation).

• Genetic controls: Test tissues from plants with altered At5g49610 expression (overexpression lines, RNAi lines).

The antibody is considered validated when it consistently shows the expected molecular weight band (approximately 37-40 kDa for At5g49610) in wild-type samples, reduced/absent signal in knockout samples, and blocked signal in peptide competition assays .

What protein extraction methods are optimal for detecting At5g49610 in different plant tissues?

Optimal extraction methods depend on the tissue type and downstream application:

For Western blot applications specifically, researchers have successfully used protein extraction buffer followed by sample dilution in 1X sample buffer supplemented with DTT, heated at 70°C for 5 minutes . Protein separation on 4-12% gradient gels provides optimal resolution for the detection of F-box proteins like At5g49610.

What controls should be included when working with At5g49610 antibodies?

Robust experimental design with appropriate controls is essential:

• Positive controls:

  • Recombinant At5g49610 protein

  • Tissues with confirmed high expression (e.g., specific developmental stages)

  • Tagged At5g49610 overexpression lines

• Negative controls:

  • Primary antibody omission

  • Non-specific IgG from the same species

  • Knockout/knockdown lines (if available)

  • Pre-immune serum

• Loading controls for Western blots:

  • Housekeeping proteins (e.g., actin, tubulin)

  • Total protein staining (e.g., Ponceau S)

• Tissue-specific controls:

  • Include multiple tissue types to confirm expected expression patterns

  • Developmental series to track expression changes

These controls help distinguish specific antibody binding from background or non-specific interactions and provide context for interpreting experimental results .

How can At5g49610 antibodies be used to study protein-protein interactions within SCF complexes?

At5g49610 antibodies can be powerful tools for investigating protein-protein interactions within SCF complexes through several advanced techniques:

• Co-immunoprecipitation (Co-IP): Using At5g49610 antibodies to pull down the protein complex followed by mass spectrometry or western blotting for known SCF components (SKP1, Cullin, RBX1).

• Proximity Ligation Assay (PLA): This technique allows visualization of protein interactions in situ by generating fluorescent signals only when two proteins are in close proximity (<40 nm).

• Bimolecular Fluorescence Complementation (BiFC): Though not directly using antibodies, this technique complements antibody-based approaches by confirming interactions identified via Co-IP.

• Chromatin Immunoprecipitation (ChIP): If At5g49610 is involved in transcriptional regulation complexes, ChIP using At5g49610 antibodies can identify associated DNA regions.

When designing these experiments, researchers should consider the dynamic nature of F-box protein interactions. For example, interactions with SKP1 are typically stable, while substrate interactions may be transient and condition-dependent. Use of proteasome inhibitors (e.g., MG132) and optimization of extraction conditions are critical for capturing relevant interactions .

What approaches can be used to identify the substrate proteins targeted by At5g49610?

Identifying substrate proteins targeted by F-box proteins like At5g49610 requires specialized approaches:

• Immunoprecipitation coupled with mass spectrometry:

  • Perform IP with At5g49610 antibodies under conditions that preserve substrate interactions

  • Treat samples with proteasome inhibitors to stabilize substrate interactions

  • Use quantitative proteomics to compare samples with and without treatments that trigger substrate recruitment

• Yeast two-hybrid screening:

  • Use At5g49610 as bait to screen plant cDNA libraries

  • Focus on the C-terminal substrate-binding domain

• Protein degradation assays:

  • Monitor protein stability of candidate substrates in wild-type vs. At5g49610 knockout lines

  • Use cycloheximide chase assays to track protein turnover rates

• In vitro ubiquitination assays:

  • Reconstitute SCF^At5g49610 complexes with purified components

  • Test ubiquitination activity on candidate substrates

These approaches can be complemented with bioinformatic analyses to identify proteins containing known degron motifs that might be recognized by At5g49610 .

How can phosphorylation status affect At5g49610 antibody recognition and experimental outcomes?

F-box proteins, including At5g49610 homologs, are frequently regulated by phosphorylation, which can significantly impact antibody recognition and experimental results:

• Epitope masking: Phosphorylation near antibody epitopes can block antibody binding, leading to false-negative results. This is particularly relevant for antibodies raised against linear epitopes.

• Conformational changes: Phosphorylation can induce structural changes that expose or hide epitopes, altering antibody recognition efficiency.

• Subcellular localization changes: Phosphorylation may trigger relocalization of At5g49610, resulting in different staining patterns in immunofluorescence experiments.

To address these challenges:

• Use phosphatase treatment of protein samples as a control experiment

• Consider using multiple antibodies targeting different regions of At5g49610

• Include phosphorylation-specific controls in experimental design

• Document sample preparation conditions carefully, especially regarding phosphatase inhibitor usage

These considerations are especially important when studying At5g49610 responses to environmental stimuli or hormone signaling, which may involve rapid phosphorylation events .

What are common issues when detecting At5g49610 in Western blots and how can they be resolved?

Researchers frequently encounter specific challenges when detecting F-box proteins like At5g49610:

For optimal resolution of At5g49610 and its isoforms, 4-12% gradient gels are recommended with extended running times. Transfer to PVDF membranes (rather than nitrocellulose) often yields better results for F-box proteins. Blocking with 2-5% non-fat milk or blocking reagent in TBS-T buffer for 1 hour at room temperature has proven effective .

How does sample preparation affect At5g49610 antibody performance in immunofluorescence studies?

Sample preparation critically influences antibody performance in immunofluorescence applications:

• Fixation method effects:

  • Paraformaldehyde (4%) preserves protein structure but may reduce epitope accessibility

  • Methanol provides better epitope access but can disrupt protein conformation

  • Glyoxal fixation may offer superior preservation of F-box protein epitopes

• Antigen retrieval considerations:

  • Heat-induced epitope retrieval (citrate buffer, pH 6.0) often improves detection

  • Enzymatic retrieval (proteinase K) can expose masked epitopes but risks tissue damage

• Permeabilization optimization:

  • Triton X-100 (0.1-0.3%) is standard but may remove membrane-associated proteins

  • Saponin (0.1%) offers gentler permeabilization that better preserves membrane associations

• Blocking parameters:

  • BSA (3-5%) reduces background without interfering with F-box protein detection

  • Normal serum (from secondary antibody species) further reduces non-specific binding

For optimal results with At5g49610 antibodies in plant tissues, a recommended protocol includes 4% paraformaldehyde fixation for 20 minutes, citrate buffer antigen retrieval, 0.2% Triton X-100 permeabilization for 10 minutes, and blocking with 5% BSA. Dilution of 1:100 has been found effective for immunofluorescence applications .

How can machine learning approaches improve antibody selection for detecting low-abundance F-box proteins like At5g49610?

Recent advances in machine learning are enhancing antibody selection for challenging targets:

• Epitope prediction algorithms:

  • Machine learning models can predict optimal epitopes for antibody generation

  • These algorithms consider protein structure, solvent accessibility, and conserved domains

  • For F-box proteins, targeting regions outside the conserved F-box domain improves specificity

• Active learning for antibody-antigen binding prediction:

  • Novel active learning strategies can predict antibody-antigen binding with reduced experimental data

  • Three recently developed algorithms have demonstrated significant improvements over random data selection

  • These approaches can reduce the number of required antigen mutant variants by up to 35%

• Out-of-distribution prediction challenges:

  • When predicting interactions between antibodies and antigens not represented in training data

  • Library-on-library approaches can identify specific interacting pairs

  • Machine learning models can analyze many-to-many relationships between antibodies and antigens

• Implementation considerations:

  • Start with small labeled subsets of data and iteratively expand

  • Focus on strategies that handle many-to-many relationships

  • Employ the Absolut! simulation framework to evaluate out-of-distribution performance

These computational approaches can significantly reduce the time and resources needed to develop effective antibodies against challenging targets like low-abundance F-box proteins.

How might integrating structural biology approaches with antibody development improve detection of At5g49610 conformational states?

Structural biology integration offers promising avenues for developing next-generation antibodies:

• Structure-guided epitope selection:

  • Using cryo-EM or X-ray crystallography data to identify accessible epitopes

  • Targeting conformational epitopes that distinguish between active/inactive states

  • Developing antibodies specific to substrate-bound vs. unbound states

• Single-domain antibody development:

  • Camelid-derived nanobodies can access epitopes unavailable to conventional antibodies

  • Their small size allows for better penetration in tissue samples

  • Potential for detecting cryptic epitopes revealed only in specific At5g49610 conformations

• Computational antibody design:

  • Using protein-protein docking simulations to predict antibody-antigen interactions

  • Optimizing complementarity-determining regions for enhanced specificity

  • Virtual screening of antibody libraries against predicted At5g49610 structures

• Integrative experimental validation:

  • Hydrogen-deuterium exchange mass spectrometry to validate antibody-epitope interactions

  • Surface plasmon resonance to quantify binding kinetics of structure-guided antibodies

  • Negative-stain EM to visualize antibody-antigen complexes

These approaches could enable development of antibodies that specifically recognize substrate-bound or post-translationally modified forms of At5g49610, providing unprecedented insights into its biological functions .

What are emerging applications of At5g49610 antibodies in plant stress response research?

F-box proteins play critical roles in plant stress responses, opening new research directions:

• Stress-induced expression profiling:

  • Using At5g49610 antibodies to track protein levels under various stress conditions

  • Comparing transcriptional vs. post-transcriptional regulation during stress

  • Investigating tissue-specific responses to abiotic and biotic stressors

• Signaling pathway dissection:

  • Investigating At5g49610's role in hormone signaling networks during stress

  • Mapping protein-protein interaction changes under stress conditions

  • Identifying stress-specific substrates targeted for degradation

• Post-translational modification dynamics:

  • Developing modification-specific antibodies (phospho-specific, ubiquitin-specific)

  • Tracking PTM changes in response to stress using quantitative immunoblotting

  • Correlating modifications with protein function and localization

• Translational applications:

  • Using At5g49610 as a biomarker for stress conditions in crop species

  • Developing high-throughput screening platforms for stress tolerance

  • Investigating conservation of F-box protein function across plant species

These applications could provide valuable insights into plant adaptation mechanisms and potentially inform breeding strategies for stress-tolerant crops .