At3g26010 Antibody

What is the At3g26010 protein and why is it significant in plant research?

At3g26010 refers to a specific gene locus in Arabidopsis thaliana (Mouse-ear cress), a model organism widely used in plant molecular biology research. The protein encoded by this gene has significance in understanding fundamental plant biological processes. Antibodies targeting this protein enable researchers to investigate its expression patterns, localization, and functional relationships within plant cellular systems. The At3g26010 protein is cataloged in the UniProt database under accession number Q9LU90, which provides researchers with access to its sequence information and known functional domains . Research using this antibody contributes to our understanding of plant development, stress responses, and evolutionary conservation of protein functions across plant species.

What are the optimal storage conditions for At3g26010 antibody to maintain its efficacy?

For optimal stability and retention of immunoreactivity, the At3g26010 antibody should be stored at either -20°C or -80°C immediately upon receipt . Repeated freeze-thaw cycles must be strictly avoided as they can lead to denaturation of the antibody structure and subsequent loss of binding capacity and specificity. The antibody is provided in liquid form with a specific storage buffer composition (50% glycerol, 0.01M PBS at pH 7.4, with 0.03% Proclin 300 as a preservative) . This formulation helps maintain stability during storage. For long-term preservation exceeding 6 months, storage at -80°C is recommended, while for routine use within shorter timeframes, -20°C is generally sufficient. Always allow the antibody to thaw completely at 4°C before use, and briefly centrifuge to collect the full volume at the bottom of the vial before opening.

Which experimental applications has the At3g26010 antibody been validated for?

The At3g26010 antibody has been specifically validated for Enzyme-Linked Immunosorbent Assay (ELISA) and Western Blotting (WB) applications . These validated applications provide researchers with reliable methods for both quantitative detection (ELISA) and qualitative assessment of protein size and expression (WB). When employing these techniques, researchers should follow standardized protocols while optimizing antibody concentrations for their specific experimental conditions. The antibody's polyclonal nature provides an advantage in recognizing multiple epitopes of the target protein, potentially enhancing signal detection. Researchers should note that while the antibody has been tested for these two primary applications, additional optimization may be required for novel experimental systems or when using the antibody in other immunological techniques beyond those explicitly validated by the manufacturer.

What is the immunogen used to produce the At3g26010 antibody and why is this information important?

The At3g26010 antibody was produced using recombinant Arabidopsis thaliana At3g26010 protein as the immunogen . This information is critically important for researchers for several reasons:

• It indicates that the antibody was raised against the full recombinant protein rather than just a peptide fragment, potentially providing recognition of multiple epitopes.

• Understanding the immunogen helps researchers assess potential cross-reactivity with related proteins, especially in experiments involving multiple plant species.

• It informs appropriate positive control selection for validation experiments, suggesting that recombinant At3g26010 protein would serve as an ideal positive control.

• Knowledge of the immunogen aids in troubleshooting experiments where unexpected binding patterns occur, allowing researchers to evaluate whether these patterns reflect true biological variation or technical limitations of the antibody.

The use of the recombinant protein as immunogen typically enhances antibody specificity when working with Arabidopsis thaliana samples, but researchers should still perform validation experiments in their specific experimental context.

How should researchers optimize Western blot protocols specifically for At3g26010 antibody detection?

Optimizing Western blot protocols for At3g26010 antibody requires systematic adjustment of multiple parameters based on the antibody's characteristics. As a polyclonal antibody raised in rabbit, this reagent typically demonstrates good sensitivity but may require specific optimization . Begin with sample preparation using a buffer containing phosphatase and protease inhibitors to preserve protein integrity. For plant tissues, use a modified extraction buffer containing 50mM Tris-HCl (pH 7.5), 150mM NaCl, 1mM EDTA, 1% Triton X-100, 0.1% SDS, and freshly added protease inhibitors.

For protein separation, use 10-12% SDS-PAGE gels, loading 20-40μg of total protein per lane. Transfer to PVDF membranes (rather than nitrocellulose) often yields better results with plant proteins. Block with 5% non-fat dry milk in TBST for 1 hour at room temperature, then incubate with At3g26010 antibody at a 1:500 to 1:2000 dilution range (requiring empirical determination for optimal signal-to-noise ratio). For detection, anti-rabbit IgG secondary antibodies conjugated to HRP work effectively, followed by ECL detection.

Critical optimization steps include:

• Testing multiple antibody dilutions (typically starting with 1:1000)

• Varying incubation times (1 hour at room temperature versus overnight at 4°C)

• Adjusting washing stringency (number of washes and TBST concentration)

• Including appropriate positive controls (Arabidopsis thaliana wild-type extracts) and negative controls (knockout mutants if available)

When analyzing results, assess both specificity (single band of expected molecular weight) and sensitivity (signal strength at different protein concentrations).

What cross-reactivity considerations should researchers account for when using At3g26010 antibody in non-Arabidopsis plant species?

While the At3g26010 antibody is specifically raised against and tested for Arabidopsis thaliana reactivity , researchers working with other plant species must carefully address cross-reactivity considerations. Cross-reactivity depends on the evolutionary conservation of epitopes recognized by the antibody across species. For closely related Brassicaceae family members (e.g., Brassica species), there may be sufficient homology to permit cross-reactivity, but this cannot be assumed without validation.

When using this antibody in non-Arabidopsis species, researchers should:

• Perform sequence homology analysis of the At3g26010 protein against the target species using BLAST or similar tools to predict potential cross-reactivity based on sequence conservation.

• Include well-characterized positive controls (Arabidopsis samples) alongside experimental samples from other species in all experiments.

• Validate specificity through complementary approaches such as immunoprecipitation followed by mass spectrometry identification or parallel analysis using knockout/knockdown lines.

• Consider epitope competition assays using recombinant At3g26010 protein to confirm binding specificity in the new species context.

• If cross-reactivity is confirmed, assess whether the antibody recognizes the same protein isoforms and post-translational modifications in the non-Arabidopsis species.

How can researchers effectively use the At3g26010 antibody in immunoprecipitation experiments for protein-protein interaction studies?

Immunoprecipitation (IP) using the At3g26010 antibody presents a powerful approach for investigating protein-protein interactions, though requiring careful optimization. While IP is not explicitly listed among the validated applications for this antibody , its polyclonal nature makes it potentially suitable for this technique. To implement an effective IP protocol:

• Begin with fresh plant tissue (preferably 1-2g), rapidly frozen in liquid nitrogen and ground to a fine powder.

• Extract proteins using a non-denaturing lysis buffer (50mM Tris-HCl pH 7.5, 150mM NaCl, 0.5% NP-40, 1mM EDTA, 3mM DTT, plus protease inhibitor cocktail).

• Clear lysates by centrifugation (14,000g, 15 minutes, 4°C) and pre-clear with Protein A agarose beads to reduce non-specific binding.

• For the IP reaction, use 2-5μg of At3g26010 antibody per 500μg of total protein, incubating overnight at 4°C with gentle rotation.

• Add Protein A agarose beads (50μl of 50% slurry) and incubate for 2-3 hours at 4°C with rotation.

• Wash beads stringently (at least 4-5 washes) with wash buffer (lysis buffer with reduced detergent concentration).

• Elute immunoprecipitated complexes using either acidic elution (0.1M glycine, pH 2.5) or by boiling in SDS sample buffer.

• Analyze precipitated complexes using SDS-PAGE followed by Western blotting or mass spectrometry.

Always include appropriate controls: IgG isotype control antibodies to assess non-specific binding, input samples (pre-IP lysate) to verify target protein presence, and when possible, samples from knockout plants as negative controls. For protein interaction discovery, consider crosslinking prior to lysis to stabilize transient interactions.

What statistical design considerations should be implemented when using antibody arrays featuring At3g26010 antibody?

When incorporating At3g26010 antibody into antibody microarrays, researchers must implement rigorous statistical design considerations to ensure reliable, reproducible, and interpretable results. Drawing from principles in antibody microarray development , the following statistical design elements are critical:

• Replication Structure: Implement both technical replicates (multiple spots per antibody on each array) and biological replicates (independent biological samples). A minimum of 3-4 biological replicates per experimental condition is recommended, with each featuring 3-5 technical replicates.

• Randomization: Apply randomization principles to array production, including randomizing spot positions and sample processing order to minimize positional and batch effects.

• Reference Sample Strategy: Utilize a common reference design where each experimental sample is compared against a universal reference sample, allowing for normalization across multiple arrays.

• Dye-Swap Experiments: For two-color antibody microarrays, implement dye-swap replicates where the dye assignments (Cy3/Cy5) are reversed between sample pairs to control for dye-specific biases.

• Power Analysis: Conduct a priori power analysis to determine the minimum number of replicates needed to detect biologically meaningful differences at a specified significance level (typically α=0.05) with adequate power (typically β≥0.8).

This structured approach to experimental design will minimize systematic biases and allow for robust statistical inference when interpreting results from antibody microarrays that include the At3g26010 antibody .

How should researchers normalize and analyze data from experiments using At3g26010 antibody in immunofluorescence studies?

For immunofluorescence (IF) studies using the At3g26010 antibody, proper normalization and analysis methods are essential to obtain quantitatively reliable results. Although IF is not explicitly listed among validated applications for this antibody , researchers may adapt it for this purpose with appropriate controls and normalization strategies.

Data Normalization Workflow:

• Background Correction: Subtract the average intensity of regions without cells/tissue from all measurements to account for non-specific fluorescence. Use multiple background regions per image for more accurate correction.

• Autofluorescence Control: Include samples processed identically but without primary antibody to quantify and subtract autofluorescence, particularly important in plant tissues which often exhibit significant autofluorescence.

• Internal Reference Normalization: Normalize At3g26010 signal to a stable reference protein or structural marker (e.g., nuclear stain, plasma membrane marker) to account for variations in cell size, morphology, and acquisition settings.

• Inter-experimental Calibration: Include a standard sample across all experimental batches to allow for inter-experiment comparisons, using this standard to calculate normalization factors.

Analysis Approaches:

• For subcellular localization: Employ co-localization analysis with known organelle markers, calculating Pearson's or Manders' coefficients to quantify the degree of spatial correlation.

• For expression level quantification: After normalization, use integrated density measurements rather than mean intensity, as this better accounts for variations in protein distribution.

• For morphological analysis: Apply threshold-based segmentation followed by particle analysis to quantify size, number, and distribution of At3g26010-positive structures.

• For statistical analysis: Analyze at least 50-100 cells per condition across 3+ biological replicates, using hierarchical statistical models that account for both cell-to-cell variation (nested within) and sample-to-sample variation.

All quantification should include appropriate quality control metrics such as signal-to-noise ratio and coefficient of variation to ensure measurement reliability.

What are the recommended protocols for validating At3g26010 antibody specificity in newly generated plant lines or mutants?

Rigorous validation of At3g26010 antibody specificity is essential when working with novel plant lines, mutants, or experimental conditions. A comprehensive validation protocol should include multiple complementary approaches to establish antibody specificity beyond reasonable doubt.

Multi-level Validation Protocol:

• Genetic Validation:

  • Compare antibody reactivity between wild-type plants and At3g26010 knockout/knockdown lines (T-DNA insertion lines, CRISPR mutants, or RNAi lines)

  • An authentic signal should be substantially reduced or eliminated in genetic knockout lines

  • For overexpression lines, signal intensity should correlate with transcript abundance

• Biochemical Validation:

  • Perform peptide competition assays using the recombinant At3g26010 protein as a competitive inhibitor

  • Pre-incubate antibody with excess immunogen before application to samples

  • Specific signals should be eliminated or significantly reduced

• Molecular Weight Validation:

  • Confirm that the detected band in Western blots matches the predicted molecular weight of At3g26010 protein

  • Account for potential post-translational modifications that may alter apparent molecular weight

  • Consider using mass spectrometry to confirm protein identity in immunoprecipitated samples

• Orthogonal Method Validation:

  • Correlate antibody-based detection with mRNA expression data (qRT-PCR or RNA-seq)

  • Compare localization patterns with fluorescent protein-tagged versions of At3g26010

  • Verify using a second antibody targeting a different epitope of the same protein (if available)

• Cross-Reactivity Assessment:

  • Test antibody against recombinant proteins with high sequence similarity

  • Examine antibody reactivity in tissues known to lack At3g26010 expression (negative control tissues)

How should researchers troubleshoot weak or absent signal when using At3g26010 antibody in Western blot applications?

When encountering weak or absent signals with At3g26010 antibody in Western blotting, a systematic troubleshooting approach is necessary to identify and resolve the issue. The following diagnostic and remedial strategies address both technical and biological factors that may affect antibody performance:

Diagnostic Framework for Signal Issues:

• Sample Preparation Assessment:

  • Verify protein extraction efficiency using protein quantification and Ponceau S staining

  • Check for protein degradation by evaluating sample handling (temperature, protease inhibitors)

  • Consider tissue-specific expression levels; certain tissues may have naturally low expression

  • Test different extraction buffers optimized for plant membrane proteins if standard lysis is insufficient

• Antibody-Related Factors:

  • Determine optimal antibody concentration through titration experiments (1:250 to 1:5000)

  • Extend primary antibody incubation time (overnight at 4°C instead of 1-2 hours)

  • Verify antibody activity with positive control samples (Arabidopsis wild-type tissue)

  • Check antibody storage conditions and avoid repeated freeze-thaw cycles

• Detection System Optimization:

  • Increase sensitivity by switching to enhanced chemiluminescence (ECL) substrate

  • Extend film exposure time or adjust imaging settings on digital systems

  • Verify secondary antibody functionality with a different primary antibody

  • Consider signal amplification systems (biotin-streptavidin enhancement)

• Protocol Modifications:

  • Reduce washing stringency (decrease salt concentration or detergent in wash buffer)

  • Change blocking agent (try BSA instead of milk or vice versa)

  • Adjust transfer conditions for more efficient protein migration to membrane

  • Consider native versus denaturing conditions if epitope recognition is affected by protein folding

If these approaches fail to resolve the issue, consider whether post-translational modifications or developmental regulation might affect epitope availability or protein expression. Additionally, validate antibody reactivity against recombinant At3g26010 protein to confirm that the antibody remains functional.

What approaches can resolve non-specific binding when using At3g26010 antibody in immunohistochemistry?

Non-specific binding represents a significant challenge when adapting the At3g26010 antibody for immunohistochemical applications. Though not explicitly validated for immunohistochemistry , when researchers employ this technique, the following comprehensive approach can effectively reduce background and enhance specific signal:

Multi-strategy Approach to Reduce Non-specific Binding:

• Blocking Optimization:

  • Test multiple blocking agents (5% normal serum from secondary antibody species, 3-5% BSA, commercial blocking buffers)

  • Extend blocking time (2-3 hours at room temperature or overnight at 4°C)

  • Add 0.1-0.3% Triton X-100 to blocking solution to reduce hydrophobic interactions

  • Consider dual blocking with both protein-based blockers and 0.1% glycine to quench free aldehyde groups from fixation

• Antibody Dilution and Incubation:

  • Determine optimal antibody concentration through serial dilution tests (1:100 to 1:2000)

  • Add 0.05-0.1% detergent (Tween-20) to antibody diluent

  • Include 1% BSA in antibody dilution buffer to reduce non-specific interactions

  • Pre-adsorb antibody with plant tissue extract from knockout plants or unrelated species

• Washing Regime:

  • Implement more stringent washing (5-6 washes of 10 minutes each)

  • Use PBS-T with increased salt concentration (up to 500mM NaCl) for high-stringency washes

  • Include a high-salt wash step (500mM NaCl in PBS) after primary antibody incubation

  • Apply detergent gradient washing (decreasing detergent concentration in successive washes)

• Controls and Validation:

  • Include No-Primary-Antibody controls to assess secondary antibody specificity

  • Process knockout/knockdown tissues alongside wild-type samples

  • Perform peptide competition assays by pre-incubating antibody with immunogen

  • Use isotype control antibodies to distinguish between specific binding and Fc receptor interactions

• Tissue Preparation Considerations:

  • Optimize fixation conditions (duration, fixative composition) to preserve antigenicity

  • Consider antigen retrieval methods if epitope masking is suspected

  • Test fresh-frozen versus fixed tissues if fixation affects epitope recognition

  • Reduce endogenous peroxidase activity with H₂O₂ treatment if using HRP-based detection

By systematically applying these strategies and documenting their effects, researchers can develop optimized protocols that maximize specific signal while minimizing background, enabling reliable localization of At3g26010 protein in plant tissues.

How can researchers effectively combine At3g26010 antibody detection with other molecular techniques for comprehensive protein function analysis?

To fully elucidate At3g26010 protein function, researchers should integrate antibody-based detection with complementary molecular techniques in a multi-modal research strategy. This integrated approach provides convergent evidence about protein function, interaction networks, and regulatory mechanisms.

Integrated Analytical Framework:

• Antibody-Based Methods Combined with Transcriptomics:

  • Correlate protein expression (Western blot/ELISA) with mRNA levels (RNA-seq/qRT-PCR)

  • Compare protein and transcript localization patterns through immunohistochemistry and in situ hybridization

  • Apply these paired analyses across developmental stages or stress conditions to identify post-transcriptional regulation

  • Calculate protein-to-mRNA ratios to quantify translational efficiency and protein stability

• Proteomics Integration:

  • Use immunoprecipitation with At3g26010 antibody followed by mass spectrometry (IP-MS) to identify interaction partners

  • Compare results with yeast two-hybrid or split-GFP assays to validate interactions

  • Implement proximity-dependent biotin identification (BioID) using At3g26010 as bait to capture transient interactions

  • Analyze post-translational modifications through IP-MS with phospho-specific or ubiquitin-specific detection

• Functional Genomics Correlation:

  • Associate antibody-detected protein levels with phenotypic data from knockout/overexpression lines

  • Conduct rescue experiments in mutant lines while monitoring protein expression levels

  • Implement CRISPR-Cas9 epitope tagging for parallel detection with both endogenous antibody and tag-specific antibodies

  • Correlate protein localization changes with functional outputs in genetic backgrounds with altered interacting partners

• Structural Biology Interface:

  • Use antibody-validated expression patterns to guide recombinant protein production for structural studies

  • Confirm that protein conformation in in vitro studies matches the native state detected by the antibody

  • Map epitope recognition to structural domains for insight into functional regions

  • Employ conformational-specific antibodies to detect structural changes under different conditions

• Systems Biology Integration:

  • Incorporate antibody-based quantification into mathematical models of relevant biological pathways

  • Use protein expression data to constrain flux analysis in metabolic pathways

  • Correlate protein levels with metabolomic data to identify functional relationships

  • Develop biosensors based on antibody-antigen interactions to monitor real-time dynamics

What emerging technologies could enhance the application of At3g26010 antibody in plant molecular research?

Several cutting-edge technologies have the potential to significantly expand the utility and precision of At3g26010 antibody applications in plant molecular research. These emerging approaches can address current limitations and open new avenues for investigating protein function in increasingly sophisticated ways.

Emerging Technological Advances:

• Single-Cell Antibody-Based Proteomics:

  • Adaptation of microfluidic platforms for single-cell Western blotting to detect At3g26010 expression in individual plant cells

  • Development of highly-multiplexed antibody panels including At3g26010 for single-cell analysis of protein co-expression patterns

  • Integration with single-cell transcriptomics for multi-omics analysis at cellular resolution

  • These approaches would reveal cell-type specific expression patterns currently masked in bulk tissue analysis

• Advanced Imaging Technologies:

  • Super-resolution microscopy (STORM, PALM) with At3g26010 antibody for nanoscale localization

  • Light-sheet microscopy for 3D imaging of protein distribution in intact plant tissues

  • Correlative light and electron microscopy (CLEM) to connect protein localization with ultrastructural context

  • Advanced image analysis using machine learning algorithms for automated quantification of complex localization patterns

• Proximity-Dependent Labeling Combined with Antibody Detection:

  • TurboID or APEX2 fusion constructs with At3g26010 for in vivo proximity labeling

  • Validation of proximity-labeled proteins using At3g26010 antibody in co-immunoprecipitation

  • Spatial-specific interaction mapping through integration of proximity labeling with tissue-specific promoters

  • This approach would map the dynamic interactome of At3g26010 in living plant cells

• Antibody Engineering Technologies:

  • Development of recombinant nanobodies against At3g26010 for improved tissue penetration

  • Creation of intrabodies (intracellular antibodies) for live-cell tracking of At3g26010

  • Site-specific antibody conjugation for precise fluorophore positioning and improved FRET applications

  • These engineered antibody formats would enhance sensitivity and enable new applications

• Integrated Multi-Modal Omics:

  • Spatial transcriptomics combined with antibody-based protein detection for spatial correlation

  • Antibody-based chromatin immunoprecipitation if At3g26010 has DNA-binding properties

  • Integration of antibody-detected protein localization with metabolite imaging for functional correlations

  • These integrated approaches would connect protein presence with functional outcomes in situ

By adopting these emerging technologies, researchers can transcend current limitations in studying At3g26010, enabling more precise spatial and temporal resolution of protein dynamics, comprehensive interaction mapping, and integration of protein function into broader biological contexts.

How can computational approaches enhance the interpretation of experimental data generated using At3g26010 antibody?

Computational approaches offer powerful methods to extract deeper insights from experimental data generated using the At3g26010 antibody. As the complexity and scale of biological data continue to increase, computational tools become essential for robust analysis and interpretation.

Advanced Computational Frameworks:

• Machine Learning for Image Analysis:

  • Convolutional neural networks (CNNs) for automated detection and quantification of At3g26010 immunostaining patterns

  • Unsupervised clustering algorithms to identify novel subcellular localization patterns

  • Transfer learning approaches that apply pre-trained models to plant cell images

  • Implementation example: Training a U-Net architecture on manually annotated immunofluorescence images to automatically segment and quantify At3g26010-positive structures across large image datasets

• Network Analysis of Protein Interactions:

  • Graph theory algorithms to analyze At3g26010 interaction networks from IP-MS data

  • Identification of key network motifs and functional modules

  • Integration of interaction data with gene ontology for functional enrichment analysis

  • Prediction of conditional interactions based on network topology

• Molecular Dynamics and Structural Prediction:

  • Ab initio protein structure prediction of At3g26010 to identify functional domains

  • Epitope mapping through computational analysis of antibody-antigen interactions

  • Molecular dynamics simulations to predict conformational changes under different conditions

  • Using these predictions to interpret unexpected antibody binding patterns

• Bayesian Statistical Frameworks:

  • Hierarchical Bayesian models to integrate multiple data sources with antibody detection

  • Probabilistic graphical models to infer causal relationships in regulatory networks

  • Accounting for technical and biological variability through explicit probability distributions

  • Increased statistical power through appropriate modeling of complex experimental designs

• Multivariate Data Integration:

  • Tensor decomposition methods for integrating multi-dimensional data (protein levels, localization, interactions across conditions)

  • Canonical correlation analysis to identify relationships between protein expression and phenotypic traits

  • Multi-block data fusion techniques to integrate antibody-derived data with other omics datasets

  • Example application: Creating a tensor representation of At3g26010 expression across tissues, development stages, and stress conditions to identify patterns not apparent in pairwise comparisons

By implementing these computational approaches, researchers can move beyond descriptive analyses to predictive models, enhancing the value of experimental data generated using the At3g26010 antibody and placing protein function within broader systems contexts.