ERF10 Antibody

What is ERF10 and why is it significant in plant research?

ERF10 (Ethylene Response Factor 10) belongs to the AP2/ERF transcription factor family involved in plant responses to various environmental stresses and developmental processes. This protein plays critical roles in ethylene signaling pathways, which affect numerous physiological processes including growth, development, and stress responses in plants. Understanding ERF10 function provides insights into plant adaptive mechanisms and stress tolerance, making it a valuable target for agricultural biotechnology research .

How does an ERF10 antibody differ from other ERF family antibodies?

ERF10 antibody is specifically designed to recognize and bind to epitopes unique to the ERF10 protein, distinguishing it from other members of the ERF family (such as ERF1A, ERF5, ERF105, ERF109, and ERF115 that are also commercially available as seen in the antibody catalogs). This specificity is crucial as the ERF family comprises multiple proteins with similar structural domains but distinct functions. The antibody's specificity is determined through epitope mapping and validation processes to ensure minimal cross-reactivity with other ERF family members, which is essential for accurate experimental outcomes in plant molecular biology research .

What validation methods should be used to confirm ERF10 antibody specificity?

Multiple validation approaches should be employed to confirm ERF10 antibody specificity:

• Western blot analysis using both wild-type and ERF10 knockout/knockdown plant tissues

• Immunoprecipitation followed by mass spectrometry

• ELISA testing against recombinant ERF10 protein and related family members

• Immunohistochemistry with appropriate negative controls

• Peptide competition assays to confirm epitope specificity

Researchers should always perform these validations in their specific experimental system, as antibody performance can vary across different applications and tissue preparations .

How can ERF10 antibody be optimized for chromatin immunoprecipitation (ChIP) experiments?

Optimizing ERF10 antibody for ChIP requires several methodological considerations:

• Crosslinking optimization: Test various formaldehyde concentrations (0.75-1.5%) and incubation times (10-20 minutes) to preserve protein-DNA interactions while maintaining epitope accessibility

• Sonication parameters: Adjust sonication conditions to produce DNA fragments of 200-500bp for optimal resolution

• Antibody titration: Perform preliminary experiments with 2-10μg of antibody per reaction to determine optimal concentration

• Pre-clearing strategy: Implement stringent pre-clearing with protein A/G beads and non-specific IgG

• Washing stringency: Develop a washing protocol that removes non-specific interactions while preserving specific binding events

Including both positive control regions (known ERF10 binding sites) and negative control regions (non-target sequences) is essential for validating ChIP results. For plant tissues, additional optimization of tissue disruption and nuclear isolation steps may be necessary to improve chromatin accessibility .

What are the critical factors affecting ERF10 antibody performance in co-immunoprecipitation studies?

Several critical factors influence ERF10 antibody performance in co-immunoprecipitation (co-IP) studies:

For plant tissue samples, incorporating protease inhibitors specific for plant proteases and performing initial experiments with stabilized protein complexes (e.g., using chemical crosslinkers) can significantly improve co-IP results with ERF10 antibody .

How can phosphorylation status of ERF10 be monitored using phospho-specific antibodies?

Monitoring ERF10 phosphorylation requires:

• Identification of phosphorylation sites: Use bioinformatics prediction tools and phosphoproteomic data to identify potential phosphorylation sites on ERF10

• Development/selection of phospho-specific antibodies: Either develop custom antibodies against phosphorylated peptides or select commercially available phospho-specific antibodies targeting conserved motifs

• Validation strategy: Confirm specificity using phosphatase-treated samples as negative controls and phosphomimetic mutants as positive controls

• Sample preparation: Incorporate phosphatase inhibitors (e.g., sodium fluoride, sodium orthovanadate) in all buffers during sample preparation

• Detection method optimization: Adjust immunoblotting conditions including blocking agents and antibody concentrations

When analyzing stress-responsive phosphorylation events, time-course experiments with appropriate controls are essential to distinguish between constitutive and induced phosphorylation states of ERF10 .

What are the optimal fixation and permeabilization protocols for ERF10 immunofluorescence studies in plant tissues?

Effective ERF10 immunolocalization in plant tissues requires optimized fixation and permeabilization:

• Fixation options:

  • 4% paraformaldehyde in PBS (pH 7.4) for 1-2 hours at room temperature

  • Alternative: 3:1 ethanol:acetic acid fixation for better nuclear protein preservation

• Permeabilization methods:

  • Cell wall digestion with 1-2% cellulase and 0.5% macerozyme for 20-30 minutes at 37°C

  • Membrane permeabilization with 0.1-0.5% Triton X-100 for 15-30 minutes

  • For thicker tissues, additional treatment with 1% driselase may improve antibody penetration

• Antigen retrieval:

  • Heat-mediated retrieval in citrate buffer (pH 6.0)

  • Enzymatic retrieval with 0.01% trypsin for 5-15 minutes

• Blocking optimization:

  • 3-5% BSA or normal serum in PBS with 0.1% Tween-20

  • Addition of 0.1% fish gelatin can reduce plant tissue-specific background

The optimal protocol should be determined empirically for each plant tissue type, as fixation requirements can vary significantly between different plant organs and developmental stages .

How should western blot protocols be modified for optimal ERF10 detection?

Optimizing western blot protocols for ERF10 detection requires several specific modifications:

• Sample preparation:

  • Include protease inhibitors specific for plant tissues

  • For nuclear proteins like ERF10, use nuclear extraction protocols with high-salt buffers (300-400mM NaCl)

  • Maintain samples at 4°C throughout processing to prevent degradation

• Gel electrophoresis conditions:

  • Use 10-12% polyacrylamide gels for optimal resolution of the ERF10 protein

  • Consider gradient gels (4-15%) when analyzing protein complexes

  • Include positive controls (recombinant ERF10) and molecular weight markers

• Transfer parameters:

  • Semi-dry transfer at 15V for 30-45 minutes or wet transfer at 30V overnight at 4°C

  • Use PVDF membranes for better protein binding and signal stability

  • Verify transfer efficiency with reversible staining (Ponceau S)

• Antibody incubation:

  • Primary antibody dilution: 1:500 to 1:2000 in 5% non-fat milk or BSA

  • Extended incubation (overnight at 4°C) for better sensitivity

  • Multiple short washing steps (5 x 5 minutes) to reduce background

• Detection optimization:

  • Enhanced chemiluminescence (ECL) for standard detection

  • Fluorescent secondary antibodies for quantitative analysis

  • Signal enhancement systems for low abundance targets

Including both positive controls (tissues known to express ERF10) and negative controls (ERF10 knockout/knockdown tissues) is essential for proper interpretation of results .

What tissue preparation methods yield optimal results for immunohistochemical detection of ERF10 in plant samples?

For optimal immunohistochemical detection of ERF10 in plant tissues:

• Sample collection and fixation:

  • Harvest tissues at consistent times to account for diurnal variation in protein expression

  • Immediate fixation in 4% paraformaldehyde or FAA (Formalin-Acetic-Alcohol) for 12-24 hours

  • For woody tissues, vacuum infiltration of fixative improves penetration

• Tissue processing:

  • Dehydration through graded ethanol series (30% to 100%)

  • Clearing with xylene or xylene substitutes

  • Paraffin embedding with careful orientation for sectioning

• Sectioning parameters:

  • 5-10μm sections for standard light microscopy

  • Mount on adhesive slides (poly-L-lysine or APTES-coated)

  • Dry sections at 37°C overnight for improved adhesion

• Antigen retrieval methods:

  • Heat-induced epitope retrieval in citrate buffer (pH 6.0)

  • For recalcitrant samples, protease digestion (0.05% trypsin, 5-15 minutes)

  • Combination approaches for difficult tissues

• Background reduction strategies:

  • Quench endogenous peroxidases with 3% H₂O₂

  • Block with 3-5% normal serum from the same species as the secondary antibody

  • Include 0.1% Triton X-100 and 0.1% Tween-20 in blocking buffers

  • Pre-absorb primary antibody with plant tissue powder from negative control samples

These methodological refinements significantly improve signal-to-noise ratio in plant immunohistochemistry applications with ERF10 antibody .

How can researchers differentiate between specific and non-specific signals when using ERF10 antibody?

Differentiating specific from non-specific signals requires a systematic approach:

• Control experiments:

  • Negative controls: omission of primary antibody, isotype controls, and pre-immune serum

  • Genetic controls: ERF10 knockout/knockdown tissues

  • Peptide competition assays: pre-incubation of antibody with immunizing peptide

• Signal characteristics analysis:

  • Signal localization: compare with known subcellular distribution of ERF10 (primarily nuclear)

  • Signal intensity: quantitative comparison across different tissues/conditions

  • Molecular weight verification: compare observed vs. predicted molecular weight in western blots

• Cross-validation methods:

  • Use multiple antibodies targeting different epitopes of ERF10

  • Confirm findings with orthogonal techniques (e.g., mass spectrometry, RNA expression)

  • Genetic complementation experiments in knockout backgrounds

• Quantitative assessment tools:

  • Signal-to-noise ratio calculation

  • Statistical analysis of replicate experiments

  • Comparison with published literature and databases

By implementing these strategies systematically, researchers can confidently distinguish between genuine ERF10 signals and experimental artifacts .

What statistical approaches are recommended for quantifying ERF10 expression levels across different experimental conditions?

For robust quantification of ERF10 expression:

• Experimental design considerations:

  • Minimum of 3-5 biological replicates per condition

  • Include technical replicates for each biological sample

  • Incorporate appropriate positive and negative controls

  • Design experiments to control for confounding variables

• Normalization strategies:

  • Use multiple reference proteins (ACTIN, TUBULIN, GAPDH) for western blot normalization

  • Implement total protein normalization (Stain-Free, Ponceau S) to avoid reference protein bias

  • Apply geometric mean of multiple references for more stable normalization

• Statistical methods for comparisons:

  • Parametric tests (t-test, ANOVA) for normally distributed data

  • Non-parametric alternatives (Mann-Whitney, Kruskal-Wallis) for non-normal distributions

  • Post-hoc tests (Tukey, Bonferroni) for multiple comparisons

  • Linear mixed models for complex experimental designs

• Data visualization approaches:

  • Box plots showing data distribution

  • Bar graphs with individual data points

  • Heat maps for multi-condition experiments

Appropriate statistics and transparent reporting of all data processing steps are essential for reproducible research with ERF10 antibody .

How should researchers address contradictory results when comparing ERF10 protein levels with transcript expression data?

Addressing discrepancies between protein and transcript levels involves:

• Verification steps:

  • Confirm antibody specificity with appropriate controls

  • Validate transcript measurements with multiple primer sets

  • Assess technical reproducibility of both protein and RNA methods

• Biological explanations to consider:

  • Post-transcriptional regulation (miRNAs, RNA stability)

  • Translational efficiency differences

  • Protein stability and degradation rates

  • Temporal delay between transcription and protein accumulation

  • Compartmentalization effects (nuclear vs. cytoplasmic fractions)

• Experimental approaches to resolve discrepancies:

  • Time-course experiments with finer resolution

  • Protein turnover studies using cycloheximide or pulse-chase experiments

  • Analysis of protein post-translational modifications

  • Polysome profiling to assess translational status

  • Subcellular fractionation to track protein localization

• Integrated data analysis:

  • Calculate protein-to-mRNA ratios across conditions

  • Apply mathematical modeling to account for synthesis and degradation rates

  • Consider multi-omics approaches incorporating proteomics, transcriptomics, and metabolomics

When protein and transcript data disagree, both measurements may be correct but reflect different regulatory mechanisms operating at different levels of gene expression. Comprehensive analysis across multiple regulatory levels often provides mechanistic insights into ERF10 function that would be missed by single-omics approaches .

How can ERF10 antibody be utilized in single-cell protein analysis of plant tissues?

Adapting ERF10 antibody for single-cell applications requires:

• Tissue preparation innovations:

  • Enzymatic protoplast isolation with optimized buffer conditions

  • Mechanical tissue disruption techniques (e.g., laser capture microdissection)

  • Preservation of cell type identity through genetic markers

• Single-cell protein detection methods:

  • Flow cytometry with fluorescently labeled ERF10 antibody

  • Mass cytometry (CyTOF) for multiplexed protein detection

  • Single-cell western blotting for quantitative analysis

  • Imaging mass spectrometry for spatial resolution

• Signal amplification strategies:

  • Tyramide signal amplification for immunofluorescence

  • Proximity ligation assays for protein-protein interaction studies

  • DNA-barcoded antibodies for digital counting applications

• Integrated multi-omics approaches:

  • Combined protein and transcript analysis from the same cells

  • Correlation of ERF10 levels with chromatin accessibility

  • Spatial transcriptomics with protein measurements

These emerging technologies enable researchers to track ERF10 dynamics at unprecedented resolution, revealing cell-type-specific responses to environmental stimuli and developmental cues that are masked in whole-tissue analyses .

What are the emerging applications of ERF10 antibody in plant stress response research?

Emerging applications include:

• Stress-specific post-translational modifications:

  • Monitoring phosphorylation, SUMOylation, and ubiquitination status of ERF10 during different stress conditions

  • Correlating modifications with transcriptional activity using ChIP-seq

  • Mapping modification sites and their functional consequences

• Protein-protein interaction networks:

  • Identification of stress-specific ERF10 interaction partners through co-IP and mass spectrometry

  • Analysis of transcriptional complex assembly/disassembly under stress

  • Quantification of interaction dynamics using FRET/FLIM approaches

• Spatiotemporal dynamics:

  • Real-time tracking of ERF10 movements between subcellular compartments during stress

  • Analysis of tissue-specific expression patterns in response to local vs. systemic stresses

  • Correlation of protein levels with physiological and metabolic indicators of stress

• Agricultural applications:

  • Screening for ERF10 expression/modification patterns associated with stress tolerance

  • Comparison of ERF10 responses across cultivars with different stress resilience

  • Development of ERF10-based biomarkers for early stress detection

• Climate change research:

  • Investigating ERF10 responses to combined stresses (e.g., heat+drought, CO₂+temperature)

  • Analyzing ERF10 dynamics under fluctuating vs. stable stress conditions

  • Comparing ERF10 behavior across species with different climate adaptations

These applications illustrate how ERF10 antibody serves as a valuable tool for understanding plant adaptation to environmental challenges, with implications for crop improvement strategies .

How can computational approaches enhance the utility of ERF10 antibody in research applications?

Computational enhancements for ERF10 antibody applications include:

• Epitope prediction and antibody design:

  • In silico prediction of optimal ERF10 epitopes based on structural data

  • Molecular dynamics simulations to assess epitope accessibility

  • Sequence conservation analysis to design antibodies with cross-species reactivity

• Image analysis automation:

  • Machine learning algorithms for automated detection of ERF10 signals

  • Quantitative analysis of subcellular distribution patterns

  • 3D reconstruction from confocal z-stacks for spatial analysis

• Network biology integration:

  • Contextualizing ERF10 within protein-protein interaction networks

  • Pathway enrichment analysis based on ERF10-associated proteins

  • Multi-omics data integration (proteomics, transcriptomics, metabolomics)

• Predictive modeling:

  • Development of mathematical models predicting ERF10 behavior under various conditions

  • Systems biology approaches to understand ERF10's role in transcriptional networks

  • Simulation of ERF10 dynamics during stress responses

• Database resources:

  • Integration with plant protein databases for comparative analysis

  • Antibody validation repositories for standardized protocols

  • ERF family expression atlases across species and conditions

Computational approaches not only enhance data extraction from ERF10 antibody experiments but also provide frameworks for hypothesis generation and experimental design optimization .