At1g67390 Antibody

What is At1g67390 and why is it significant in plant research?

At1g67390 refers to a specific gene locus in Arabidopsis thaliana, encoding a protein with the UniProt identifier Q9FYF4. This protein appears to be related to the Rieske-type iron-sulfur protein family, which includes the pheophorbide a oxygenase (PaO) . The protein is of particular interest in plant research because of its potential involvement in chlorophyll catabolism and cell death pathways in plants. Research suggests it may be homologous to the Accelerated Cell Death 1 (ACD1) protein, which plays crucial roles in programmed cell death and stress responses in plants . Understanding this protein's function can provide insights into fundamental plant physiological processes, including senescence, stress responses, and developmental pathways.

What validated applications exist for the At1g67390 Antibody?

The At1g67390 Antibody has been validated for several research applications:

The antibody has been specifically tested and validated for ELISA and Western blot applications, ensuring reliable antigen identification . For optimal results in any application, performing antibody titration experiments is strongly recommended to determine the ideal working concentration for your specific experimental conditions.

What are the recommended storage and handling procedures?

For optimal antibody performance and longevity, follow these storage and handling guidelines:

• Upon receipt, store the antibody at -20°C or -80°C

• Avoid repeated freeze-thaw cycles as these can degrade antibody quality

• The antibody is supplied in liquid form in a specific storage buffer: 50% Glycerol, 0.01M PBS (pH 7.4), with 0.03% Proclin 300 as a preservative

• When handling the antibody, use aseptic technique to prevent contamination

• Prior to use in experiments, centrifuge the antibody solution at 14,000×g at 2-8°C for 10 minutes to remove any potential aggregates

• Carefully pipette from the supernatant, avoiding the bottom of the tube

• For long-term storage of working dilutions, consider adding carrier proteins (e.g., BSA) to prevent adsorption to tube walls

These procedures will help maintain antibody activity and specificity throughout your research project.

How should I optimize the antibody concentration for my experiments?

Antibody optimization is critical for generating reliable and reproducible results:

• Perform a titration experiment using serial dilutions of the antibody

• For Western blotting:

  • Test a range of antibody concentrations (e.g., 1:500, 1:1000, 1:2000, 1:5000)

  • Include positive and negative controls

  • Analyze signal-to-noise ratio at each concentration

  • Select the dilution that provides clear specific signal with minimal background

• For ELISA:

  • Use a checkerboard titration approach with varying antigen and antibody concentrations

  • Plot signal intensity versus antibody concentration

  • Identify the optimal concentration that provides maximum specific signal with minimal non-specific binding

For proteogenomic analysis applications, the suggested starting amount for titration is ≤1.0 μg per million cells in 100 μL volume . Document all optimization experiments thoroughly to ensure reproducibility across your research project.

What controls should I include when working with At1g67390 Antibody?

Incorporating appropriate controls is essential for accurate data interpretation:

How can At1g67390 Antibody be integrated into multi-omics approaches?

Integrating antibody-based detection with multi-omics approaches can provide comprehensive insights into protein function:

• Proteogenomics integration: The At1g67390 Antibody can be conjugated with oligonucleotides (similar to TotalSeq™ technology) for single-cell protein and RNA co-detection . This approach allows simultaneous examination of protein expression and transcriptome data at the single-cell level.

• ChIP-seq applications: If modified for chromatin immunoprecipitation, the antibody could potentially identify genome-wide binding sites if the protein has DNA-binding capabilities.

• Protein-protein interaction networks:

  • Use the antibody for co-immunoprecipitation followed by mass spectrometry

  • Identify interaction partners in different physiological conditions

  • Map protein complexes during various developmental stages

• Spatial proteomics:

  • Combine with cell fractionation to determine subcellular localization

  • Use for immunofluorescence microscopy to visualize tissue-specific expression patterns

  • Correlate with transcriptomic data for spatial expression analysis

• Functional validation:

  • Use for protein depletion studies in conjunction with phenotypic assays

  • Correlate protein levels with metabolomic changes during stress responses

When planning multi-omic experiments, consider technical compatibility and sample preparation requirements carefully. For example, if combining with RNA-seq, ensure fixation methods preserve both protein epitopes and RNA integrity .

What are the potential cross-reactivity concerns with At1g67390 Antibody?

Understanding potential cross-reactivity is crucial for accurate data interpretation:

• Homologous proteins: The polyclonal nature of this antibody means it recognizes multiple epitopes on the At1g67390 protein. This may lead to cross-reactivity with structurally similar proteins, particularly other Rieske-type iron-sulfur proteins in Arabidopsis or related plant species.

• Species cross-reactivity: While the antibody is specifically raised against Arabidopsis thaliana protein, it may cross-react with homologous proteins in closely related plant species. The species reactivity is officially listed as Arabidopsis thaliana , but testing in other plant models should be conducted if cross-species application is desired.

• Isoform specificity: If the At1g67390 gene produces multiple protein isoforms through alternative splicing, the antibody may detect all or only specific isoforms, depending on the location of the immunogen sequence.

To address cross-reactivity concerns:

• Perform Western blot analysis using multiple plant tissues and species

• Include samples from knockout or knockdown plants as negative controls

• Consider epitope mapping to identify the specific regions recognized by the antibody

• For critical experiments, validate results using alternative detection methods or a second antibody targeting a different epitope

How can I validate At1g67390 Antibody specificity in my experimental system?

Rigorous validation ensures reliable experimental results:

• Genetic validation:

  • Compare antibody signal between wild-type and At1g67390 knockout/knockdown plants

  • Use CRISPR-Cas9 edited plants with specific mutations in the antibody epitope region

  • Test in transgenic plants with tagged versions of the target protein

• Biochemical validation:

  • Perform peptide competition assays by pre-incubating the antibody with excess immunizing peptide

  • Conduct immunoprecipitation followed by mass spectrometry to confirm target protein identity

  • Compare results with an alternative antibody targeting a different epitope of the same protein

• Expression correlation:

  • Compare protein detection patterns with mRNA expression data across tissues and conditions

  • Correlate antibody signal intensity with quantitative PCR or RNA-seq data

• Technical validation:

  • Test specificity across multiple applications (Western blot, ELISA, immunofluorescence)

  • Evaluate batch-to-batch consistency if using multiple antibody lots

  • Document all validation experiments with appropriate controls

A comprehensive validation approach increases confidence in experimental results and facilitates troubleshooting if inconsistencies arise.

What techniques can be used to study At1g67390 protein interactions?

Understanding protein interactions provides crucial insights into biological function:

• Co-immunoprecipitation (Co-IP):

  • Use At1g67390 Antibody to pull down the protein complex

  • Identify interacting partners by Western blot or mass spectrometry

  • Compare interaction profiles under different physiological conditions

• Proximity labeling:

  • Generate fusion proteins with BioID or APEX2

  • Use the antibody to confirm expression of the fusion protein

  • Identify proximal proteins through streptavidin pulldown and mass spectrometry

• Fluorescence techniques:

  • Perform Fluorescence Resonance Energy Transfer (FRET) with labeled interaction partners

  • Use in situ Proximity Ligation Assay (PLA) to visualize interactions in fixed tissue

  • Combine with immunofluorescence to determine subcellular localization of interactions

• Crosslinking studies:

  • Use chemical crosslinkers to stabilize transient interactions

  • Immunoprecipitate with At1g67390 Antibody

  • Identify crosslinked partners by mass spectrometry

• Split-reporter systems:

  • Generate fusion constructs with split fluorescent proteins or luciferase

  • Use the antibody to validate expression levels

  • Monitor interaction dynamics in real-time

When studying protein interactions, consider the native cellular environment and potential disruption of interactions during sample preparation. Membrane proteins or weakly interacting partners may require specialized approaches to preserve interactions during extraction and analysis.

How does the polyclonal nature of At1g67390 Antibody affect experimental interpretation?

Understanding the implications of polyclonal antibody characteristics is essential for proper data analysis:

To address these considerations:

• Establish rigorous validation protocols for each new antibody lot

• Document specific experimental conditions that optimize performance

• Consider generating monoclonal antibodies for highly specific applications or quantitative analyses

• For critical experiments, verify results with orthogonal methods

How can I troubleshoot weak or absent signal when using At1g67390 Antibody?

Methodical troubleshooting can resolve common detection issues:

For Western blot specific troubleshooting:

• Try longer transfer times for high molecular weight proteins

• Use different membrane types (PVDF vs. nitrocellulose)

• Consider enhanced chemiluminescence (ECL) substrates with higher sensitivity

• Optimize blocking conditions (BSA vs. non-fat milk)

For ELISA specific troubleshooting:

• Test different plate coating buffers and conditions

• Optimize antigen concentration for coating

• Evaluate different detection systems for improved sensitivity

How can I adapt At1g67390 Antibody for advanced microscopy techniques?

Integrating this antibody with advanced imaging requires careful optimization:

• Super-resolution microscopy:

  • Consider direct labeling with small fluorophores to minimize the probe size

  • For STORM/PALM, ensure high signal-to-noise ratio through optimized blocking and washing

  • For STED microscopy, select photostable fluorophores compatible with depletion lasers

  • Validate specificity in fixed samples before proceeding with complex imaging experiments

• Live-cell imaging:

  • Consider generating Fab fragments for better tissue penetration

  • Minimize phototoxicity by using optimized labeling ratios

  • Validate that labeling doesn't interfere with protein function

  • Combine with fluorescent protein fusions for dual validation

• Expansion microscopy:

  • Test antibody compatibility with expansion protocols

  • Optimize fixation to preserve epitopes through the expansion process

  • Consider using fluorophores stable under expansion conditions

  • Validate specificity and signal retention after expansion

• Correlative light and electron microscopy (CLEM):

  • Use gold-conjugated secondary antibodies for electron microscopy detection

  • Optimize sample preparation to preserve ultrastructure and epitope accessibility

  • Consider pre-embedding labeling for improved sensitivity

  • Validate specificity at both light and electron microscopy levels

• Technical considerations:

  • Use fiducial markers for image registration in multimodal imaging

  • Optimize fixation protocols to preserve both structure and antigenicity

  • Consider tissue clearing techniques for deep tissue imaging

  • Implement quantitative analysis workflows for objective signal evaluation

How can At1g67390 Antibody be used to investigate stress response mechanisms in plants?

Investigating stress responses requires systematic experimental design:

• Stress treatment protocols:

  • Apply standardized abiotic stressors (drought, salt, heat, cold, etc.)

  • Use pathogen infection or elicitor treatments for biotic stress

  • Implement time-course experiments to capture dynamic responses

  • Compare protein levels across different tissues and developmental stages

• Protein expression analysis:

  • Monitor At1g67390 protein levels by Western blot before, during, and after stress

  • Correlate protein abundance with physiological parameters

  • Compare with transcriptomic data to identify post-transcriptional regulation

  • Use phytohormone treatments to dissect signaling pathways

• Protein localization studies:

  • Track subcellular localization changes during stress response

  • Combine with organelle markers to confirm compartmentalization

  • Investigate potential stress-induced protein translocation

  • Correlate localization with protein function

• Protein modifications:

  • Investigate post-translational modifications using specific antibodies

  • Combine immunoprecipitation with mass spectrometry to identify modifications

  • Analyze modification patterns across stress conditions

  • Correlate modifications with protein activity or localization changes

• Functional studies:

  • Compare wild-type and knockout/knockdown plants under stress conditions

  • Analyze phenotypic differences and survival rates

  • Investigate downstream molecular changes

  • Develop mechanistic models of protein function during stress response

This systematic approach can provide comprehensive insights into the role of At1g67390 protein in plant stress responses, potentially revealing novel stress adaptation mechanisms.

What bioinformatic tools can help analyze data generated using At1g67390 Antibody?

Integrating experimental data with bioinformatic analysis enhances biological insights:

• Sequence analysis tools:

  • Use BLAST and multiple sequence alignment to identify homologs across species

  • Predict protein domains and functional motifs using InterPro or PFAM

  • Analyze evolutionary conservation patterns to identify functional regions

  • Predict potential post-translational modification sites

• Structural analysis:

  • Use AlphaFold or similar tools to predict protein structure

  • Identify potential interaction interfaces or functional domains

  • Map epitope regions recognized by the antibody

  • Model potential conformational changes under different conditions

• Omics data integration:

  • Correlate protein abundance with transcriptomic data across conditions

  • Use tools like Cytoscape for network analysis of protein interactions

  • Integrate with metabolomic data to identify associated metabolic pathways

  • Apply machine learning approaches for pattern recognition across datasets

• Visualization and analysis platforms:

  • Use R/Bioconductor packages for statistical analysis and visualization

  • Implement Python libraries for custom data analysis pipelines

  • Apply specialized plant biology databases (TAIR, Araport, BAR) for contextual information

  • Utilize gene ontology enrichment tools to identify functional patterns

• Advanced analysis approaches:

  • Apply single-cell analysis methods when combining with technologies like CITE-seq

  • Use systems biology modeling to predict protein behavior under different conditions

  • Implement temporal analysis for time-course experiments

  • Develop custom algorithms for specific experimental designs

Effective bioinformatic analysis can transform raw experimental data into meaningful biological insights, enabling hypothesis generation for further investigation.

How can At1g67390 Antibody be used in comparative plant biology studies?

Exploring protein conservation and divergence across species:

• Cross-species reactivity testing:

  • Test antibody reactivity with homologous proteins in related plant species

  • Optimize extraction and detection protocols for each species

  • Identify conserved epitopes through sequence alignment and experimental validation

  • Document cross-reactivity patterns for reference

• Evolutionary analysis:

  • Compare protein expression patterns across evolutionary diverse plant species

  • Correlate protein conservation with functional conservation

  • Identify lineage-specific adaptations or modifications

  • Analyze cellular localization across species to detect functional divergence

• Stress response comparison:

  • Compare protein expression under identical stress conditions across species

  • Identify conserved and divergent stress response mechanisms

  • Correlate protein behavior with species-specific stress tolerance

  • Develop evolutionary models of stress adaptation

• Developmental biology:

  • Compare protein expression during key developmental stages across species

  • Identify conserved developmental roles and species-specific functions

  • Analyze tissue-specific expression patterns

  • Correlate protein function with morphological or physiological adaptations

• Methodological considerations:

  • Standardize extraction protocols to ensure comparable results

  • Develop quantitative normalization approaches for cross-species comparison

  • Consider generating species-specific standard curves for quantitative analyses

  • Validate findings with orthogonal approaches (e.g., mass spectrometry)

Comparative studies can reveal fundamental insights into plant evolution and adaptation, potentially identifying conserved mechanisms with agricultural or ecological significance.

Future Research Directions

Emerging technologies and methodological advances offer exciting opportunities for expanding the utility of At1g67390 Antibody:

• Integration with single-cell technologies may provide unprecedented insights into cell-type specific expression patterns

• Combination with CRISPR-Cas9 gene editing for precise functional studies

• Application in proteogenomic approaches for multi-omics data integration

• Development of improved antibody formats with enhanced specificity or sensitivity

• Adaptation for high-throughput screening applications