KEGG: ath:AT2G40995
STRING: 3702.AT2G40995.1
At2g40995 is a gene in Arabidopsis thaliana (Mouse-ear cress) that encodes a defensin-like protein 107 belonging to the molecular chaperone Hsp40/DnaJ family protein . Defensin-like proteins typically function in plant defense mechanisms, while Hsp40/DnaJ family proteins serve as molecular chaperones that assist in protein folding, assembly, and translocation processes. Current research suggests potential roles for At2g40995 in stress response pathways, though specific functions need further characterization through targeted experimental approaches.
The primary research applications for At2g40995 antibody include:
These techniques allow researchers to investigate At2g40995 protein expression, localization, and interactions within plant systems, providing essential insights into its biological functions.
Currently available At2g40995 antibodies have the following specifications:
These characteristics should be considered when selecting an appropriate antibody for specific experimental designs and research questions.
Proper validation is critical for ensuring reliable experimental results:
Western Blot Validation:
Compare wild-type Arabidopsis samples with At2g40995 knockout/knockdown lines
Verify single band at the expected molecular weight
Test for cross-reactivity with related defensin-like or Hsp40/DnaJ family proteins
Peptide Competition Assay:
Pre-incubate antibody with the immunizing peptide
Compare signal with and without peptide competition
Significant signal reduction confirms specificity
Multiple Antibody Validation:
Use antibodies targeting different epitopes of At2g40995
Compare detection patterns across experimental conditions
Recombinant Protein Controls:
Test against purified recombinant At2g40995
Include related proteins as negative controls
To maintain antibody functionality:
| Parameter | Recommended Conditions |
|---|---|
| Storage Temperature | -20°C for long-term; 4°C for working aliquots |
| Buffer Composition | PBS with 50% glycerol and preservative (e.g., 0.02% sodium azide) |
| Aliquoting | Small single-use aliquots (10-20μl) to prevent freeze-thaw cycles |
| Freeze-Thaw Cycles | Limit to maximum of 3 cycles |
| Working Dilutions | Prepare fresh and store at 4°C for no more than 1 week |
| Shipping Conditions | On ice packs or dry ice |
Proper storage and handling practices maintain antibody specificity and sensitivity, ensuring consistent experimental results across studies.
Recent research on genotype-environment associations (GEA) in Arabidopsis provides a framework for investigating At2g40995's potential role in drought adaptation:
Protein Expression Profiling:
Compare At2g40995 protein expression between drought-sensitive and drought-resistant ecotypes
Analyze expression patterns during progressive drought stress
Correlate protein levels with physiological drought response markers
Protein Interaction Networks:
Use At2g40995 antibody for co-immunoprecipitation followed by mass spectrometry
Identify drought-specific interaction partners
Map protein complexes formed under drought stress conditions
Integration with GEA Data:
Correlate At2g40995 protein levels with allelic variants identified in GEA studies
Examine protein expression in the context of genotype-by-environment (GxE) interactions
Assess post-translational modifications in response to moisture gradients
These approaches can help determine whether At2g40995, like the drought-responsive genes WRKY38 and LSD1 identified in recent studies, contributes to adaptive drought responses in Arabidopsis .
Antibody phage display offers powerful approaches for developing highly specific At2g40995 antibodies:
Library Construction Strategy:
Selection (Panning) Protocol:
Immobilize recombinant At2g40995 protein on solid support
Perform 3-4 rounds of selection with increasing stringency
Include negative selection steps with related proteins to enhance specificity
Clone Screening and Validation:
Analyze monoclonal phage by ELISA against At2g40995 and related proteins
Sequence promising clones to determine VH and VL sequences
Express soluble scFv for functional characterization
| Panning Round | Antigen Concentration | Washing Stringency | Elution Method |
|---|---|---|---|
| Round 1 | 10μg/ml | 5× PBST (0.1% Tween) | pH elution (2.2) |
| Round 2 | 5μg/ml | 10× PBST (0.1% Tween) | pH elution (2.2) |
| Round 3 | 1μg/ml | 15× PBST (0.5% Tween) | Competitive elution |
Recent advances in antibody design have demonstrated that precise, specific antibodies can be developed without prior antibody information, using yeast display scFv libraries of approximately 10⁶ sequences .
Distinguishing At2g40995 from related proteins requires careful experimental design:
Epitope Mapping:
Identify unique regions in At2g40995 compared to other defensin-like proteins
Design peptide arrays covering the entire At2g40995 sequence
Map the specific epitopes recognized by the antibody
Cross-Reactivity Testing:
Express and purify recombinant At2g40995 and related defensin-like proteins
Perform systematic Western blot and ELISA testing across all family members
Quantify relative binding affinities to each protein
Genetic Validation:
Use At2g40995 knockout/knockdown lines as negative controls
Compare antibody reactivity in wild-type vs. mutant tissues
Perform complementation with tagged At2g40995 variants
Competitive Binding Assays:
Pre-incubate antibodies with purified At2g40995 or related proteins
Compare signal reduction patterns to quantify cross-reactivity
Develop absorption protocols to enhance specificity
Integrating protein-level data with genetic and environmental analyses requires sophisticated analytical approaches:
Multi-Omics Data Integration:
Correlate At2g40995 protein levels with transcriptomic and metabolomic data
Implement network analysis to identify functional modules
Use machine learning to predict environmental response patterns
Statistical Methods for GxE Analysis:
Apply mixed linear models integrating protein expression and genetic variation
Use structural equation modeling to map causal relationships
Implement Bayesian approaches to estimate effect sizes
| Analysis Stage | Recommended Methods | Purpose |
|---|---|---|
| Data Preprocessing | Normalization, outlier detection | Ensure data quality and comparability |
| Association Testing | Linear mixed models, GWAS | Identify genotype-protein-environment relationships |
| Network Analysis | Weighted correlation networks | Map functional relationships |
| Visualization | Interactive plots, heatmaps | Interpret complex relationships |
Recent GEA studies in Arabidopsis have successfully integrated genetic and environmental data to identify drought-responsive genes (e.g., WRKY38, LSD1), providing a methodological framework for studying At2g40995 .
Investigating stress-induced post-translational modifications (PTMs) of At2g40995:
Modification-Specific Detection:
Develop or obtain antibodies specific to common PTMs (phosphorylation, ubiquitination)
Compare modified vs. total At2g40995 levels under stress conditions
Map modification sites using mass spectrometry
Subcellular Dynamics:
Track At2g40995 localization changes during stress response
Correlate localization with modification status
Examine co-localization with known stress response components
Functional Significance Assessment:
Express wild-type vs. modification-site mutant versions of At2g40995
Compare protein-protein interactions of modified vs. unmodified protein
Assess impact of modifications on protein stability and turnover
Temporal Profiling:
Create detailed time-course analyses of modifications during stress progression
Correlate modification patterns with physiological stress markers
Identify regulatory enzymes controlling At2g40995 modifications
These approaches can reveal how post-translational regulation of At2g40995 contributes to plant stress responses, particularly in drought adaptation contexts where genotype-by-environment interactions have been observed .
Successful immunoprecipitation requires attention to several critical factors:
Sample Preparation:
Use optimized extraction buffers compatible with plant tissues
Include protease/phosphatase inhibitors to preserve protein modifications
Consider native vs. denaturing conditions based on experimental goals
Antibody Selection and Coupling:
Evaluate polyclonal vs. monoclonal antibodies for IP efficiency
Consider direct antibody labeling vs. protein A/G beads
Optimize antibody-to-lysate ratios through titration experiments
Control Implementation:
Include non-immune IgG controls from the same species
Use At2g40995 knockout/knockdown samples as negative controls
Consider pre-clearing lysates to reduce non-specific binding
Validation Approaches:
Confirm successful IP by Western blot of input, unbound, and eluted fractions
Verify enrichment of At2g40995 by quantitative comparison to input
Validate interacting partners through reciprocal co-IP experiments
These methodological considerations help ensure reliable and reproducible immunoprecipitation results when studying At2g40995 protein interactions.
Optimizing antibody phage display for At2g40995-specific antibodies:
Library Design Considerations:
Selection Strategy Optimization:
Employ decreasing antigen concentrations across panning rounds
Implement off-rate selection to identify high-affinity binders
Use alternating selection surfaces to reduce non-specific binders
Screening Approaches:
Develop high-throughput competition ELISA for specificity assessment
Implement surface plasmon resonance for affinity determination
Use next-generation sequencing to track selection enrichment
Antibody Engineering:
Convert promising scFv to full IgG format for enhanced functionality
Optimize framework regions for stability and expression
Consider affinity maturation through targeted mutagenesis
Recent advances in de novo antibody design have demonstrated success in generating antibodies with tailored properties, suggesting promising approaches for At2g40995-specific antibody development .
Recent breakthroughs in computational antibody design offer promising approaches:
Structure-Based Design:
Use protein structure prediction to model At2g40995
Identify optimal epitopes for antibody binding
Design complementary binding interfaces in antibody variable regions
Library-Based Approaches:
Create rational designed antibody libraries targeting At2g40995 epitopes
Combine computational design with yeast display screening
Implement machine learning to predict binding properties
De Novo Design Methods:
Apply atomic-accuracy structure prediction to design specific binders
Create libraries combining designed light and heavy chain sequences
Screen resulting libraries for binders with desired properties
Recent research demonstrates that precise, sensitive, and specific antibody design can be achieved without prior antibody information, with designed antibodies exhibiting affinity, activity, and developability comparable to commercial antibodies .
Emerging research on genotype-environment associations provides a framework for investigating At2g40995's potential role:
Allele Frequency Analysis:
Examine At2g40995 allele distribution across moisture gradients
Compare sequence variation between drought-prone and moisture-rich habitats
Identify potentially adaptive polymorphisms
Functional Validation Approaches:
Use knockout/knockdown lines to test for drought-related phenotypes
Measure stomatal conductance and specific leaf area under drought conditions
Assess flowering time responses to moisture variation
Population Genomics Integration:
Analyze signatures of selection around the At2g40995 locus
Compare with known drought adaptation loci like WRKY38 and LSD1
Identify potential regulatory variants affecting expression
Recent experimental validation of genotype-environment associations in Arabidopsis has identified genes contributing to local adaptation to drought conditions, providing methodological frameworks applicable to studying At2g40995's potential adaptive roles .
Advancing the field requires collaborative approaches:
Validation Data Sharing:
Publish comprehensive antibody validation data
Deposit detailed protocols in repositories like Protocols.io
Share negative results to prevent duplication of effort
Resource Development:
Create knockout and epitope-tagged lines for antibody validation
Develop and share recombinant protein standards
Establish benchmark datasets for antibody performance evaluation
Methodological Innovations:
Apply emerging antibody engineering technologies to improve specificity
Develop new validation approaches for plant antibodies
Create standardized reporting formats for antibody characterization
Community Standards Development:
Establish minimum validation requirements for plant antibodies
Create data sharing frameworks for antibody characterization
Develop quality metrics for commercial and academic antibody resources