Host species and clonality: Rabbit polyclonal antibody (AS11 1747), affinity-purified for specificity .
Immunogen: Synthetic peptide derived from Arabidopsis thaliana DHAR1 sequence (Q9FRL8, At1g75270), conjugated to KLH .
Physical properties:
| Parameter | Specification |
|---|---|
| Recommended dilution | 1:5,000 (Western blot) |
| Tested applications | Western blot (WB) |
| Reactivity | Arabidopsis thaliana (confirmed); Ricinus communis, Populus trichocarpa (predicted) |
DHAR2 antibody enabled detection of sulfenylation (Cys20 oxidation) under H₂O₂ stress using dimedone tagging and Western blotting . This revealed:
GSH-mediated protection: 1 mM glutathione (GSH) reduced sulfenylation by forming S-glutathionylated DHAR2 .
Kinetic analysis: DHAR2 exhibits positive cooperativity (Hill coefficient = 2.65) with a k<sub>cat</sub>/K<sub>0.5</sub> of 9.3 × 10⁵ M⁻¹·s⁻¹ .
H₂O₂ effects: Activity decreased by 60% at 5 mM H₂O₂, partially rescued by GSH .
Cys20 modification: Identified as the primary sulfenylation site via LC-MS/MS .
Overoxidation: Irreversible sulfonic acid formation occurred at >1 mM H₂O₂ without GSH .
Redox regulation: DHAR2 maintains ascorbate pools, critical for mitigating oxidative damage .
Stress induction: Upregulated by jasmonic acid and abiotic stressors (e.g., salinity, drought) .
Electrophoresis: 15% SDS-PAGE
Transfer: 1 hr semidry blot to PVDF (Bjerrum buffer)
Detection: AP-conjugated secondary antibody (1:2,000) with NBT/BCIP staining
| Feature | DHAR2 | DHAR1 | DHAR3 |
|---|---|---|---|
| K<sub>M</sub> | 23.8 µM | 260 µM | 500 µM |
| Localization | Cytoplasm | Chloroplast | Peroxisome |
| Stress response | H₂O₂, jasmonates | Light stress | Pathogen challenge |
DHAR2 (Dehydroascorbate Reductase 2) is a critical enzyme in plants involved in the ascorbate-glutathione cycle, which plays an essential role in antioxidant defense systems. In Arabidopsis thaliana, DHAR2 (At1g75270) helps maintain redox homeostasis by catalyzing the reduction of dehydroascorbate to ascorbate using glutathione as a reducing agent.
Antibodies against DHAR2, such as polyclonal antibodies raised in rabbits using KLH-conjugated synthetic peptides derived from the DHAR sequence, are crucial research tools that enable:
Monitoring DHAR2 expression levels under various stress conditions
Determining subcellular localization through immunohistochemistry
Studying protein-protein interactions via co-immunoprecipitation
Evaluating post-translational modifications
Researchers targeting plant stress physiology, redox biology, and antioxidant systems frequently employ these antibodies to advance understanding of plant responses to environmental stressors .
Verifying antibody specificity is a critical step before conducting extensive experiments. For DHAR2 antibodies, implement the following validation protocol:
Western blot with positive and negative controls:
Positive control: Recombinant DHAR2 protein or extract from wild-type plants
Negative control: Extract from DHAR2 knockout/knockdown plants
Cross-reactivity assessment:
Test against purified related proteins (DHAR1, DHAR3)
Compare banding patterns with predicted molecular weights
Peptide competition assay:
Pre-incubate antibody with excess immunizing peptide
Signal should be significantly reduced in Western blot
Immunoprecipitation followed by mass spectrometry:
Confirm pulled-down protein is indeed DHAR2
Correlation with transcript levels:
Compare protein detection with RT-qPCR results in different conditions
This multi-approach validation ensures that experimental observations are truly attributable to DHAR2 and not to cross-reactivity with related proteins .
Optimized Western blot protocol for DHAR2 antibody detection:
Sample Preparation:
Extract proteins in buffer containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 1 mM EDTA with freshly added protease inhibitors
For plant tissues, add 10 mM DTT and 1% PVPP to reduce interference from phenolic compounds
Gel Electrophoresis and Transfer:
Use 12-15% SDS-PAGE gels (DHAR2 is approximately 23-25 kDa)
Transfer to PVDF membrane at 100V for 60 minutes in 10% methanol transfer buffer
Antibody Incubation:
Blocking: 5% non-fat dry milk in TBS-T (1 hour at room temperature)
Primary antibody: Dilute DHAR2 antibody 1:1000 to 1:2000 in 1% BSA/TBS-T
Incubation: Overnight at 4°C with gentle rocking
Secondary antibody: Anti-rabbit HRP at 1:5000 dilution (1 hour at room temperature)
Detection and Troubleshooting:
Use ECL substrate for standard detection
Expected band: ~23-25 kDa for Arabidopsis DHAR2
If background is high, increase washing time and reduce primary antibody concentration
For weak signals, extend primary antibody incubation and use high-sensitivity ECL substrate
This protocol has been validated across multiple plant species and tissue types with consistent results .
Successful immunolocalization of DHAR2 in plant tissues requires careful protocol optimization:
Tissue Preparation:
Fix tissue in 4% paraformaldehyde in PBS (pH 7.4) for 2-4 hours
Embedded in paraffin or resin depending on required resolution
For whole-mount preparations, use 2% paraformaldehyde with 0.1% glutaraldehyde
Antigen Retrieval:
Perform heat-induced epitope retrieval in 10 mM sodium citrate buffer (pH 6.0)
Alternative: Enzymatic retrieval with 0.01% trypsin in PBS for 10-15 minutes at 37°C
Immunostaining Protocol:
Blocking: 5% normal goat serum, 1% BSA in PBS with 0.1% Triton X-100 (2 hours)
Primary antibody: Dilute DHAR2 antibody 1:100 to 1:200 in blocking buffer
Incubation: 12-16 hours at 4°C in a humid chamber
Secondary antibody: Fluorophore-conjugated anti-rabbit IgG at 1:300 dilution
Controls and Visualization:
Negative controls: Pre-immune serum and secondary antibody-only samples
For co-localization studies, pair with established organelle markers:
Chloroplast: anti-RbcL
Peroxisome: anti-catalase
Cytosol: anti-GAPDH (cytosolic isoform)
Results Interpretation:
DHAR2 typically shows cytosolic and chloroplastic localization patterns
Confirm specificity by comparing with subcellular fractionation results and GFP fusion studies
This optimized protocol minimizes background staining while maximizing specific DHAR2 detection .
| Problem | Potential Causes | Solutions |
|---|---|---|
| No signal in Western blot | - Protein degradation - Poor transfer - Insufficient antibody concentration | - Add fresh protease inhibitors - Verify transfer with Ponceau staining - Increase antibody concentration to 1:500 |
| Multiple bands | - Protein degradation - Post-translational modifications - Cross-reactivity | - Use fresher samples - Add phosphatase inhibitors - Perform peptide competition assay |
| High background | - Insufficient blocking - Too high antibody concentration - Inadequate washing | - Extend blocking to 2 hours - Dilute antibody further (1:3000-1:5000) - Add 0.2% Tween-20 to washing buffer |
| Variable results between replicates | - Sample preparation inconsistency - Storage conditions affecting antibody - Protein expression variability | - Standardize extraction protocol - Aliquot antibody and avoid freeze-thaw cycles - Normalize to loading controls |
| Weak signal | - Low protein abundance - Protein masked by fixation - Antibody deterioration | - Concentrate samples using TCA precipitation - Try alternative fixation methods - Order fresh antibody |
Each troubleshooting approach should be systematically documented to identify the specific variables affecting your experimental system. Creating standardized protocols with internal controls significantly improves reproducibility when working with DHAR2 antibodies across different plant stress conditions and developmental stages .
When DHAR2 protein levels detected by antibodies contradict enzyme activity measurements, consider these potential explanations and resolution strategies:
Potential Causes of Discrepancies:
Post-translational Modifications
Phosphorylation, glutathionylation, or oxidation may alter DHAR2 activity without changing protein abundance
Resolution: Combine Western blots with Phos-tag gels or redox proteomics techniques
Protein-Protein Interactions
DHAR2 activity can be regulated by protein partners not detectable in standard assays
Resolution: Perform co-immunoprecipitation followed by activity assays of the complex
Substrate/Cofactor Availability
In vivo glutathione limitations may restrict activity despite high protein levels
Resolution: Measure GSH/GSSG ratios in corresponding samples
Compartmentalization Effects
DHAR2 may be sequestered in different cellular compartments affecting its activity
Resolution: Combine immunolocalization with subcellular fractionation and activity assays
Methodological Approach for Resolution:
Perform parallel analysis of DHAR2 protein levels (Western blot), transcript abundance (RT-qPCR), and enzyme activity under identical conditions
Assess protein turnover rates using cycloheximide chase experiments
Evaluate the redox state of the cellular environment
Consider isoform-specific activities if multiple DHAR enzymes are present
This comprehensive analysis approach helps determine whether discrepancies represent technical artifacts or genuine biological regulation mechanisms, such as post-translational activity control .
DHAR2 antibodies can significantly enhance mass spectrometry-based proteomics studies through several advanced applications:
Immunoprecipitation-Mass Spectrometry (IP-MS):
Use DHAR2 antibodies conjugated to magnetic beads or protein A/G
Enrich DHAR2 and associated proteins from complex cellular extracts
Perform on-bead digestion with trypsin before LC-MS/MS analysis
Identify DHAR2 interaction partners under various stress conditions
Selected Reaction Monitoring (SRM) Enhancement:
Develop SRM assays targeting DHAR2-specific peptides identified through antibody-based enrichment
Create a spectral library of DHAR2 peptides for accurate quantification
Enhance detection sensitivity by 10-100 fold through preliminary immunoenrichment
Post-Translational Modification Mapping:
Enrich DHAR2 using specific antibodies
Analyze enriched fractions using LC-MS/MS with neutral loss scanning for phosphorylation
Apply electron transfer dissociation (ETD) for precise localization of modifications
Workflow Implementation:
Optimize DHAR2 antibody binding conditions for maximum specificity
Perform parallel immunoprecipitations with specific antibody and non-specific IgG control
Analyze eluates using high-resolution MS (Orbitrap or Q-TOF)
Apply SAINT or similar statistical models to identify high-confidence interactors
Validate key interactions through reciprocal co-immunoprecipitation
This approach has revealed that DHAR2 interacts with components of the ascorbate-glutathione cycle and stress-responsive signaling proteins, providing deeper insights into redox signaling networks in plants .
Developing machine learning models for DHAR2-related disease detection using antibody-derived peptides involves several sophisticated approaches:
Data Acquisition and Preparation:
Compile DHAR2 antibody sequence datasets from sources like OAS (Observed Antibody Space)
Perform in silico digestion to generate theoretical peptide fragments
Remove peptides present in common databases to identify unique signature peptides
Create databases of varying sizes (10² to 10⁷ peptides) to optimize search space and minimize false discovery rates
Mass Spectrometry Data Processing:
Process MS data using database search algorithms (e.g., Mascot, SEQUEST)
Apply target-decoy approach to control false discovery rate
Implement spectral matching techniques for peptide identification
Validate identifications using synthetic peptide standards
Machine Learning Model Development:
Feature extraction from MS/MS spectra and antibody sequence patterns
Apply dimensionality reduction techniques (PCA, t-SNE)
Test multiple algorithms:
Support Vector Machines
Random Forests
Deep Neural Networks (particularly CNN for spectral data)
Implement k-fold cross-validation to assess model performance
Validation and Performance Metrics:
Sensitivity and specificity in distinguishing disease states
Area Under ROC Curve (AUC) for model comparison
Positive Predictive Value for clinical relevance assessment
Example Performance Comparison:
| ML Algorithm | Accuracy | Sensitivity | Specificity | AUC |
|---|---|---|---|---|
| Random Forest | 87.3% | 83.5% | 90.2% | 0.91 |
| SVM (RBF kernel) | 85.1% | 80.2% | 89.5% | 0.89 |
| CNN | 92.7% | 89.3% | 94.1% | 0.95 |
| Ensemble | 94.5% | 91.2% | 95.8% | 0.97 |
This approach leverages the unique peptide signatures derived from DHAR2 antibodies to develop diagnostic tools with potential applications in plant stress detection, offering a promising avenue for translating fundamental research into practical biotechnology applications .
A systematic approach to investigate cross-reactivity between DHAR2 antibodies and other DHAR family members requires careful experimental design:
Perform multiple sequence alignment of all DHAR family proteins
Identify regions of high similarity that may cause cross-reactivity
Map known epitopes recognized by the antibody
Use computational tools to predict potential cross-reactive epitopes
Clone and express all DHAR family members (DHAR1, DHAR2, DHAR3) with appropriate tags
Purify proteins under native conditions to maintain structural integrity
Quantify protein concentration accurately using BCA or Bradford assays
ELISA-based quantification:
Coat plates with equal amounts (100 ng/well) of each DHAR protein
Test DHAR2 antibody at multiple dilutions (1:500 to 1:10,000)
Calculate relative affinity for each protein
Western blot analysis:
Load equivalent amounts (25-50 ng) of each recombinant protein
Perform Western blotting with standardized conditions
Quantify band intensity using densitometry
Calculate cross-reactivity ratios
Surface Plasmon Resonance (SPR):
Immobilize DHAR2 antibody on sensor chip
Flow solutions containing each DHAR protein
Determine binding kinetics (kon, koff) and affinity constants (KD)
Analyze extracts from wild-type plants and single/multiple DHAR knockout lines
Perform immunoprecipitation followed by mass spectrometry to identify pulled-down proteins
Use immunofluorescence in plant tissues with known differential expression of DHAR isoforms
This comprehensive approach provides quantitative data on cross-reactivity potential, enabling researchers to correctly interpret experimental results and design appropriate controls for DHAR2-specific studies .
Distinguishing between changes in DHAR2 protein abundance and post-translational modifications requires a multi-faceted experimental approach:
Comprehensive Experimental Design:
Parallel Western Blot Analysis:
Standard Western blot for total DHAR2 protein
Phos-tag™ PAGE for phosphorylated forms
Non-reducing gels for detection of S-glutathionylation
2D gels (IEF/SDS-PAGE) to separate modified isoforms
Mass Spectrometry-Based Approaches:
DHAR2 immunoprecipitation followed by tryptic digestion
Parallel analysis with:
Standard peptide detection for abundance
Neutral loss scanning for phosphorylation
Precursor ion scanning for glutathionylation
MS^3 for complex modifications
Targeted Post-Translational Modification Detection:
Phosphorylation: Use phospho-specific antibodies if available
Redox modifications: OxiRAC methodology to detect cysteine oxidation
Ubiquitination: Use anti-ubiquitin antibodies following DHAR2 immunoprecipitation
Activity Correlation Studies:
Measure DHAR2 enzyme activity in parallel samples
Correlate changes in activity with specific modifications
Use site-directed mutagenesis of key residues to confirm functional impact
Data Integration Framework:
| Parameter | Technical Approach | Output Data | Integration |
|---|---|---|---|
| Total Protein | Quantitative Western blot | Normalized band intensity | Baseline reference |
| Phosphorylation | Phos-tag™ gel + MS/MS | Modified residues and stoichiometry | % of total protein phosphorylated |
| S-glutathionylation | Non-reducing gels + MS | Modified cysteines | Correlation with oxidative stress |
| Protein turnover | Cycloheximide chase | Degradation rate | Distinguish synthesis vs. degradation |
| Enzyme activity | Spectrophotometric assay | Specific activity | Activity:protein ratio indicates regulation |
This integrated approach enables researchers to determine whether changes in DHAR2 function result from altered protein abundance or from specific post-translational modifications that affect activity, localization, or interaction with partner proteins .
DHAR2 antibodies provide powerful tools for investigating plant responses to emerging climate stressors through various advanced research approaches:
Temporal and Spatial Profiling of Stress Responses:
Use DHAR2 antibodies to track protein expression patterns during:
Extreme temperature fluctuations
Drought-flood cycles
Elevated CO₂ conditions
Combined stresses that mimic future climate scenarios
Implement high-throughput immunoblotting across tissue types and developmental stages
Stress Priming and Memory Studies:
Track DHAR2 protein levels during:
Initial stress exposure
Recovery phase
Subsequent stress challenge
Correlate protein abundance with ascorbate redox state and ROS signatures
Investigate epigenetic modifications affecting DHAR2 expression during recurrent stress
Field-to-Lab Translation:
Collect field samples from plants experiencing natural climate extremes
Preserve samples with specialized fixatives that maintain protein modifications
Analyze DHAR2 expression and modification patterns using antibody-based techniques
Correlate findings with controlled laboratory experiments
Multi-Omics Integration Framework:
Combine antibody-detected DHAR2 protein data with:
Transcriptomics (RNA-seq)
Metabolomics (ascorbate/dehydroascorbate ratios)
Physiological measurements (photosynthetic efficiency)
Growth parameters (biomass accumulation)
This integrated approach provides a comprehensive understanding of how redox homeostasis mechanisms respond to complex climate stress scenarios, potentially identifying DHAR2 regulatory patterns as biomarkers for stress resilience in crop improvement programs .
Developing DHAR2 antibody arrays for high-throughput phenotyping requires innovative methodological approaches that combine immunological techniques with advanced detection systems:
Array Development Strategy:
Antibody Immobilization Options:
Nitrocellulose-coated glass slides for standard arrays
3D hydrogel surfaces for enhanced binding capacity
Microfluidic channels for dynamic interaction studies
Quantum dot-conjugated surfaces for enhanced sensitivity
Multiplex Design Considerations:
Include antibodies against:
Total DHAR2 protein
Phosphorylated DHAR2 (multiple sites)
Other ascorbate-glutathione cycle enzymes
Stress-responsive marker proteins
Incorporate internal normalization controls
Sample Preparation Protocol:
High-throughput protein extraction using robotics
Standardized buffer system optimized for maintaining protein modifications
Fluorescent labeling for detection
Optional: fractionate samples to reduce complexity
Data Acquisition and Analysis Pipeline:
Automated image capture using high-resolution scanners
Signal quantification with dedicated software
Statistical analysis for large-scale comparisons
Machine learning algorithms for pattern recognition
Application Workflow for Plant Phenotyping:
| Stage | Methodology | Expected Outcome |
|---|---|---|
| Sample Collection | Automated leaf punches from multiple genotypes/treatments | 96-384 samples per batch |
| Protein Extraction | Robotic processing in deep-well plates | Standardized extracts |
| Array Probing | Automated handling with optimized incubation times | Consistent signal development |
| Data Acquisition | Fluorescence scanning at multiple wavelengths | Multi-parameter dataset |
| Data Analysis | Custom algorithms for pattern recognition | Stress response clustering |
| Validation | Secondary assays on selected samples | Confirmation of array findings |
This high-throughput approach enables:
Screening hundreds of genotypes for DHAR2-related stress responses
Temporal analysis of protein abundance and modifications
Identification of superior genotypes with enhanced redox homeostasis
Discovery of novel regulatory patterns in antioxidant networks
The resulting phenotypic data can directly inform breeding programs targeting climate resilience through enhanced antioxidant capacity .
The application of DHAR2 antibodies in plant stress biology is evolving rapidly, with several emerging trends shaping future research directions:
Single-Cell Immunodetection:
Adaptation of flow cytometry techniques for plant protoplasts
Development of in situ proximity ligation assays for detecting DHAR2 interactions at cellular resolution
Integration with microfluidic plant-on-chip platforms for real-time monitoring
Antibody Engineering for Enhanced Specificity:
Development of recombinant antibody fragments (scFv, Fab) against DHAR2
CRISPR-based epitope tagging for enhanced detection specificity
Nanobody development for improved penetration into plant tissues
Integrative Multi-Stress Analysis:
High-throughput immunoassays for screening DHAR2 responses across stress combinations
Correlation of DHAR2 dynamics with global redox state markers
Network analysis integrating DHAR2 with other stress response pathways
Translational Applications:
Development of field-deployable immunochromatographic strips for rapid DHAR2 quantification
Establishment of DHAR2 protein levels as biomarkers for stress resistance breeding
Application in crop improvement programs targeting climate resilience
These emerging approaches are enabling researchers to move beyond traditional laboratory studies toward systems-level understanding of antioxidant defense mechanisms and their contribution to plant survival under increasingly complex environmental stressors .
Advances in antibody research methodologies are poised to transform future studies of DHAR2 in plant systems through several innovative approaches:
Technological Innovations and Their Applications:
Synthetic Antibody Development:
Phage display libraries specifically designed for plant protein targets
In silico antibody design based on DHAR2 epitope mapping
Non-animal-derived recombinant antibodies with enhanced specificity
Spatiotemporal Detection Systems:
Antibody-based biosensors for real-time tracking of DHAR2 in living plants
Optogenetic reporter systems linked to antibody binding events
Super-resolution microscopy with specially modified antibodies
Multiplexed Analysis Platforms:
Digital spatial profiling combining DHAR2 antibodies with transcriptomic markers
Mass cytometry (CyTOF) adapted for plant cells with metal-labeled antibodies
Single-cell proteomics with antibody-based enrichment
Computational Integration:
Machine learning algorithms for antibody epitope prediction
Molecular dynamics simulations of antibody-DHAR2 interactions
Network analysis integrating antibody-detected protein changes with metabolic pathways
Impact on Scientific Understanding:
These methodological advances will enable researchers to:
Detect previously unobservable post-translational modifications
Determine DHAR2 protein half-life and turnover rates during stress
Identify cell-specific variations in DHAR2 function
Discover novel interactions between DHAR2 and signaling pathways
Establish causal relationships between DHAR2 activity and stress tolerance
Future Research Framework:
| Technical Advance | Impact on DHAR2 Research | Scientific Outcome |
|---|---|---|
| Single-molecule detection | Quantification of low-abundance modified forms | Detailed regulatory mechanisms |
| In situ proximity assays | Visualization of protein complexes in native tissue | Contextual understanding of interactions |
| Computational epitope mapping | Improved antibody design | Enhanced specificity for related proteins |
| Microfluidic arrays | High-throughput phenotyping | Population-level variation analysis |