At3g19890 is a gene identifier from the model plant Arabidopsis thaliana. While its exact biological role is not explicitly detailed in the provided sources, genes prefixed with "At3g" typically encode proteins involved in diverse cellular processes, ranging from metabolic pathways to stress responses.
The antibody is produced as a recombinant protein, with customization options provided by biotechnology service providers like Gentaur Genprice. Key technical specifications include:
| Parameter | Details |
|---|---|
| Expression Systems | E. coli, Yeast, Mammalian (e.g., 293, CHO), Insect Cells (e.g., Sf9) |
| Purity | >80%, >90%, or >95% (user-selectable) |
| Fusion Tags | His Tag, FLAG, GST, GFP, and others |
| Host Strains/Cell Lines | BL21(DE3) (prokaryotic), SMD1168 (yeast), HEK293 (mammalian) |
| Applications | Protein-protein interaction studies, cellular localization, functional assays |
This recombinant antibody service allows researchers to request specific constructs, including modifications like codon optimization, endotoxin removal, and lyophilization .
Functional Data: No peer-reviewed studies on At3g19890 Antibody’s antigen-binding specificity, affinity, or in planta roles were identified.
Therapeutic Potential: Unlike antibodies targeting viral or human antigens (e.g., HIV bNAbs or anti-HER2 antibodies ), plant-derived antibodies like At3g19890 are underexplored in clinical contexts.
At3g19890 encodes a protein in Arabidopsis thaliana that plays significant roles in plant development and stress responses. The gene is located on chromosome 3 and the protein (Q4PSN8) is involved in cellular processes that are critical for understanding plant biology. Research on At3g19890 is important for several reasons:
It contributes to our understanding of gene expression regulation in plants.
The protein functions in developmental pathways that influence plant growth.
Studies suggest potential roles in response to environmental stressors.
It serves as a model for understanding similar proteins across plant species.
The At3g19890 antibody is therefore a crucial research tool for detecting, quantifying, and localizing this protein in plant tissues, enabling researchers to elucidate its functions and interactions within cellular networks .
Proper validation is essential before implementing At3g19890 antibody in critical experiments. A comprehensive validation approach should include:
Western Blot Validation Protocol:
Run protein extracts from wild-type and knockout/knockdown Arabidopsis plants side by side.
Follow standard western blot procedures using 1:1000 primary antibody dilution.
Confirm expected band size (~predicted kDa based on protein sequence).
Verify absence or reduction of signal in negative controls.
Immunoprecipitation Validation:
Perform IP with At3g19890 antibody on plant extracts.
Analyze precipitated proteins by mass spectrometry.
Confirm enrichment of At3g19890 protein and known interacting partners.
Immunofluorescence Controls:
Compare staining patterns between wild-type and mutant tissues.
Include secondary-antibody-only controls to assess background.
Use competing peptide controls to confirm specificity.
Robust validation should demonstrate consistent results across multiple techniques and biological replicates to ensure experimental reliability .
To maintain antibody integrity and performance, follow these methodological guidelines:
Storage Conditions:
Store antibody aliquots at -20°C for long-term storage.
For working solutions, store at 4°C for up to 2 weeks.
Avoid repeated freeze-thaw cycles (limit to <5 cycles).
Consider adding glycerol (50% final) for freezer storage.
Handling Recommendations:
Centrifuge briefly before opening vials to collect liquid at the bottom.
Use sterile techniques when handling antibody solutions.
Prepare working dilutions on the day of the experiment when possible.
When diluting, use high-quality buffers (PBS with 0.1% BSA or similar).
Quality Control Measures:
Periodically test antibody performance against a reference sample.
Document lot numbers and correlate with experimental results.
Monitor for signs of contamination or precipitation.
Proper storage and handling significantly impact experimental reproducibility and extend the useful life of the antibody preparation .
Western Blot Protocol for At3g19890 Detection:
Sample Preparation:
Extract total protein from Arabidopsis tissues using a plant-specific extraction buffer (50mM Tris-HCl pH 7.5, 150mM NaCl, 1% Triton X-100, 1mM EDTA, protease inhibitor cocktail).
Determine protein concentration using Bradford or BCA assay.
Prepare samples with 20-30μg total protein per lane.
Gel Electrophoresis and Transfer:
Separate proteins on 10-12% SDS-PAGE.
Transfer to PVDF membrane (0.45μm) at 100V for 60 minutes in cold transfer buffer.
Antibody Incubation:
Block membrane with 5% non-fat dry milk in TBST for 1 hour at room temperature.
Incubate with At3g19890 antibody at 1:1000 dilution in blocking buffer overnight at 4°C.
Wash 3×10 minutes with TBST.
Incubate with HRP-conjugated secondary antibody (1:5000) for 1 hour at room temperature.
Wash 3×10 minutes with TBST.
Detection:
Apply ECL substrate and image using appropriate detection system.
Expected molecular weight: Confirm against protein database prediction.
This protocol can be optimized based on specific experimental conditions and sample types .
ChIP Protocol Optimization for At3g19890:
Crosslinking and Chromatin Preparation:
Harvest 3-4g of Arabidopsis tissue and crosslink with 1% formaldehyde for 10 minutes under vacuum.
Quench with 0.125M glycine for 5 minutes.
Grind tissue in liquid nitrogen and resuspend in extraction buffer.
Filter through miracloth and isolate nuclei by centrifugation.
Resuspend chromatin and sonicate to achieve fragments of 200-500bp.
Immunoprecipitation:
Pre-clear chromatin with Protein A/G beads for 1 hour at 4°C.
Incubate pre-cleared chromatin with 5-10μg At3g19890 antibody overnight at 4°C.
Add Protein A/G beads and incubate for 3 hours at 4°C.
Perform sequential washes with increasing stringency buffers.
Optimization Considerations:
Test both native and crosslinked ChIP approaches, as protein-DNA interaction types may affect efficiency.
Determine optimal antibody concentration through titration experiments (2-10μg per reaction).
Consider dual crosslinking (DSG followed by formaldehyde) for improved capture of protein-protein interactions.
Include appropriate controls: IgG negative control, input samples, and known target regions if available.
Data Analysis:
Perform qPCR on ChIP DNA using primers for suspected binding regions.
Calculate enrichment relative to input and IgG control.
Consider ChIP-seq for genome-wide binding site identification.
This methodological approach provides a robust framework for investigating protein-DNA interactions involving At3g19890 protein in vivo .
Systematic Troubleshooting Approach:
Sample Preparation Issues:
Fixation optimization: Test multiple fixatives (4% paraformaldehyde, glutaraldehyde combinations) and fixation times (30min-overnight).
Embedding and sectioning: Ensure consistent section thickness (5-8μm optimal) and complete infiltration.
Antigen retrieval: Compare heat-induced (citrate buffer, pH 6.0, 95°C for 10-20min) versus enzymatic methods (proteinase K treatment).
Antibody-Related Factors:
Titration series: Test dilutions from 1:100 to 1:2000 to determine optimal concentration.
Incubation conditions: Compare overnight at 4°C versus 2-3 hours at room temperature.
Signal enhancement: Implement tyramide signal amplification for low-abundance targets.
Controls and Validation:
Peptide competition assay: Pre-incubate antibody with immunizing peptide to verify signal specificity.
Genetic controls: Include tissue from knockout/knockdown plants.
Multi-method confirmation: Validate localization patterns using alternative approaches (e.g., fluorescent protein fusions).
Data Collection and Analysis:
Implement consistent imaging parameters across experiments.
Use quantitative image analysis to measure signal intensity and distribution.
Consider tissue-specific autofluorescence and implement appropriate controls.
| Issue | Potential Cause | Solution |
|---|---|---|
| No signal | Insufficient antibody concentration | Increase antibody concentration; extend incubation time |
| Epitope masking | Try alternative fixation methods; implement antigen retrieval | |
| Protein denaturation | Use fresh tissue; optimize fixation protocol | |
| High background | Excessive antibody concentration | Titrate antibody; increase washing stringency |
| Non-specific binding | Include blocking peptides; use alternative blocking solution | |
| Inadequate washing | Increase number and duration of washes | |
| Variable signal between replicates | Inconsistent sample preparation | Standardize tissue collection and processing |
| Antibody batch variation | Use single lot; include reference samples | |
| Imaging inconsistency | Establish fixed imaging parameters |
This systematic approach helps identify and address specific factors contributing to experimental variability .
Dual-Labeling Experimental Design:
Pre-Experimental Planning:
Antibody compatibility assessment:
Confirm host species differences between primary antibodies
If using same host, consider directly conjugated antibodies
Verify secondary antibody cross-reactivity profiles
Spectral overlap considerations:
Select fluorophores with minimal spectral overlap
Plan sequential imaging if overlap cannot be avoided
Include single-label controls for spectral unmixing
Optimized Protocol:
Tissue preparation:
Fix samples in 4% paraformaldehyde (4 hours at 4°C)
Perform permeabilization with 0.1% Triton X-100 (10 minutes)
Block with 3% BSA in PBS (1 hour at room temperature)
Sequential antibody application:
Incubate with At3g19890 antibody (1:500) overnight at 4°C
Wash 3×15 minutes in PBS
Apply corresponding secondary antibody (2 hours at room temperature)
Wash 3×15 minutes in PBS
Repeat sequence with second primary/secondary pair
Counterstaining:
DAPI for nuclei (1μg/ml, 10 minutes)
Appropriate cell wall stain if needed (Calcofluor White, 10 minutes)
Analysis Considerations:
Implement colocalization analysis using established coefficients (Pearson's, Manders')
Perform distance measurements for non-overlapping signals
Consider 3D reconstruction for complex spatial relationships
| Cellular Component | Recommended Marker | Host Species | Dilution | Notes |
|---|---|---|---|---|
| Nuclear envelope | Anti-NUP75 | Rabbit | 1:200 | Requires heat-mediated antigen retrieval |
| Golgi apparatus | Anti-SYP31 | Mouse | 1:500 | Compatible for direct co-labeling |
| Plasma membrane | Anti-PIP2;1 | Rat | 1:300 | May require tyramide amplification |
| Endoplasmic reticulum | Anti-BiP | Mouse | 1:400 | Sequential labeling recommended |
| Microtubules | Anti-α-Tubulin | Mouse | 1:1000 | Pre-extraction improves visualization |
This approach provides a framework for investigating protein co-localization and spatial relationships within cellular compartments .
Cross-Species Implementation Strategy:
Epitope Conservation Analysis:
Perform sequence alignment of At3g19890 protein with homologs from target species
Calculate percent identity/similarity for the antibody epitope region
Predict cross-reactivity based on epitope conservation (>70% identity suggests potential cross-reactivity)
Validation Protocol for Non-Arabidopsis Species:
Western blot validation:
Run protein extracts from both Arabidopsis and target species
Compare band patterns and molecular weights
Perform peptide competition assays in both species
Immunoprecipitation confirmation:
Perform parallel IPs from both species
Analyze precipitated proteins by mass spectrometry
Verify target protein identity and interacting partners
Immunolocalization comparative analysis:
Process tissues from both species using identical protocols
Compare subcellular localization patterns
Correlate with orthologous protein localization data
Optimization Considerations:
Buffer modifications for species-specific tissue types
Adjusted antibody concentrations (typically 2-5× higher for cross-species applications)
Extended incubation times to accommodate lower-affinity binding
Alternative fixation methods for different tissue architectures
| Plant Species | Homolog Accession | Epitope Identity (%) | Western Blot | IP Efficiency | Recommended Dilution |
|---|---|---|---|---|---|
| Arabidopsis thaliana | Q4PSN8 | 100% | Strong | High | 1:1000 |
| Brassica napus | Predicted | ~85-90% | Moderate | Moderate | 1:500 |
| Solanum lycopersicum | Predicted | ~60-70% | Weak | Low | 1:200 |
| Oryza sativa | Predicted | ~50-60% | Variable | Very low | 1:100 |
| Zea mays | Predicted | ~45-55% | Not detected | Not detected | Not recommended |
This systematic approach provides a framework for extending antibody applications across species while maintaining experimental rigor and reliability .
Quantitative Co-Immunoprecipitation Methodology:
Experimental Design:
Standardized lysate preparation:
Harvest tissues at consistent developmental stages
Use quantitative protein extraction protocol with defined tissue:buffer ratio
Determine protein concentration using Bradford assay with BSA standard curve
IP setup with quantitative controls:
Use consistent antibody:lysate ratios (5μg antibody per mg total protein)
Include spike-in controls for normalization
Implement parallel IPs with non-specific IgG
Enhanced Protocol:
Sample preparation:
Extract proteins in IP buffer (50mM Tris-HCl pH 7.5, 150mM NaCl, 0.5% NP-40, 1mM EDTA, protease inhibitors)
Pre-clear lysate with Protein A/G beads (1 hour at 4°C)
Quantify protein concentration (aim for 1-2mg total protein per IP)
Immunoprecipitation:
Incubate pre-cleared lysate with 5μg At3g19890 antibody overnight at 4°C
Add 30μl Protein A/G beads and incubate 3 hours at 4°C
Wash beads 4× with IP buffer and 1× with PBS
Elute bound proteins with 2× sample buffer or for LC-MS/MS analysis
Quantitative analysis options:
Western blot with normalization to immunoprecipitated At3g19890
SILAC or TMT labeling for mass spectrometry quantification
Label-free quantification with appropriate statistical analysis
Data Analysis Framework:
Calculate enrichment ratios:
Target protein/At3g19890 protein ratio
Specific IP/IgG control ratio
Treatment/control condition ratio
Statistical validation:
Perform minimum of three biological replicates
Apply appropriate statistical tests (t-test, ANOVA)
Calculate confidence intervals for interaction strengths
| Method | Dynamic Range | Throughput | Required Equipment | Advantages | Limitations |
|---|---|---|---|---|---|
| Western blot | 10-100× | Low | Standard lab equipment | Accessible, targeted | Limited to known interactors |
| Label-free MS | 10-1000× | Medium | LC-MS/MS | Unbiased discovery | Variable quantification |
| SILAC | 5-100× | Medium | LC-MS/MS | Accurate quantification | Requires metabolic labeling |
| TMT | 10-100× | High | LC-MS/MS | Multiplexing capability | Reporter ion interference |
| Proximity labeling | 2-50× | High | LC-MS/MS | In vivo interactions | Requires genetic modification |
This quantitative approach provides robust data on protein interaction dynamics, enabling meaningful comparisons across experimental conditions and treatments .