At4g35733 Antibody

What is At4g35733 and why are antibodies against it important for research?

At4g35733 refers to a specific gene locus in the Arabidopsis thaliana genome. Antibodies developed against proteins encoded by this gene are valuable tools for studying its expression, localization, and function within plant tissues. These antibodies enable researchers to conduct immunoprecipitation, Western blotting, immunohistochemistry, and other immunological techniques to understand the role of this gene in plant development, stress responses, or other biological processes. Monoclonal antibodies offer high specificity for epitopes on the target protein, helping researchers precisely track protein expression patterns across different experimental conditions .

What expression systems are recommended for generating recombinant At4g35733 protein for antibody production?

For plant proteins like those encoded by At4g35733, several expression systems can be utilized depending on research requirements. Bacterial systems (particularly E. coli) are commonly used for generating partial recombinant proteins with tags like GST that facilitate purification. For proteins requiring post-translational modifications, eukaryotic expression systems such as yeast, insect cells, or plant-based expression systems may be more appropriate. The choice should be guided by the protein's characteristics, including size, solubility, and whether native conformational epitopes need to be preserved for antibody recognition .

How should At4g35733 antibodies be validated before use in experiments?

Thorough validation is essential before using antibodies in critical experiments. For At4g35733 antibodies, validation should include:

• Western blot analysis using both recombinant protein and native plant extracts

• Testing on wild-type versus knockout/knockdown plant tissues

• Immunoprecipitation followed by mass spectrometry to confirm target specificity

• Cross-reactivity testing with related proteins to ensure specificity

• Epitope mapping to identify the recognized sequence

Additionally, antibodies should be tested in all applications where they will be used, as performance can vary between techniques. Detailed validation records should be maintained as they're crucial for result interpretation and troubleshooting .

What storage conditions maximize the shelf life of At4g35733 antibodies?

To maximize antibody shelf life and maintain activity, follow these storage guidelines:

• Store concentrated antibodies (supernatants or purified) at -20°C or -80°C for long-term storage

• For periods less than one month, storage at 4°C is typically acceptable

• Aliquot antibodies to avoid repeated freeze-thaw cycles which can degrade protein structure

• Include appropriate preservatives (such as sodium azide) for solutions stored at 4°C

• Store in appropriate buffer conditions (commonly phosphate buffered saline, pH 7.2)

• Monitor for precipitates or color changes that might indicate deterioration

Proper labeling with antibody details, concentration, date prepared, and expiration information is essential for laboratory management .

How can epitope interference be addressed when At4g35733 antibodies show unexpected cross-reactivity with other plant proteins?

When At4g35733 antibodies exhibit cross-reactivity with unintended targets, several approaches can address this challenge:

• Perform comprehensive epitope mapping to identify the specific sequence recognized by the antibody

• Analyze sequence homology between At4g35733 and potential cross-reactive proteins using bioinformatics tools

• Develop competitive blocking assays using synthetic peptides matching the epitope

• Consider using multiple antibodies targeting different epitopes of At4g35733 to confirm results

• Implement pre-adsorption protocols with recombinant proteins containing the cross-reactive epitopes

A methodical approach to addressing cross-reactivity involves systematically identifying the source of interference and developing specific protocols to mitigate it. This may include redesigning experiments to include appropriate controls or generating new antibodies with improved specificity .

What strategies can overcome detection challenges when At4g35733 protein is expressed at low levels?

Low-abundance proteins present significant detection challenges. For At4g35733, consider these approaches:

• Signal amplification techniques:

  • Tyramide signal amplification for immunohistochemistry

  • Poly-HRP conjugated secondary antibodies

  • Biotin-streptavidin amplification systems

• Sample enrichment methods:

  • Subcellular fractionation to concentrate the target protein

  • Immunoprecipitation prior to Western blotting

  • Protein concentration methods appropriate for plant tissues

• Enhanced detection systems:

  • Chemiluminescence with extended exposure times

  • Digital imaging systems with high sensitivity

  • Fluorescence-based detection with appropriate filters

• Consider creating transgenic plants with epitope-tagged versions of At4g35733 for easier detection when native antibodies provide insufficient sensitivity .

How can researchers distinguish between post-translational modifications of At4g35733 using antibody-based approaches?

Detecting and distinguishing post-translational modifications (PTMs) of At4g35733 requires specialized antibody approaches:

• Modification-specific antibodies:

  • Use antibodies specifically raised against the modified form (phosphorylated, glycosylated, etc.)

  • Compare detection patterns with antibodies recognizing the non-modified protein

• Enzymatic treatments:

  • Treat samples with phosphatases, glycosidases, or other enzymes to remove specific modifications before antibody detection

  • Observe changes in binding patterns or mobility shifts

• Two-dimensional electrophoresis:

  • Separate proteins by isoelectric point and molecular weight

  • Use antibodies to detect different modified forms appearing as distinct spots

• Mass spectrometry validation:

  • Combine immunoprecipitation with mass spectrometry analysis

  • Map modifications and their positions to correlate with antibody recognition patterns

This multi-technique approach provides robust evidence for PTM presence and distribution .

What methodological adaptations are needed when using At4g35733 antibodies with different plant species beyond Arabidopsis?

Cross-species application of At4g35733 antibodies requires careful methodological considerations:

• Sequence homology analysis:

  • Compare protein sequences between species to predict conservation of epitopes

  • Focus on antibodies targeting highly conserved regions

• Protocol modifications:

  • Adjust extraction buffers to accommodate differences in cellular composition

  • Modify blocking agents to reduce background in different tissues

  • Alter incubation times and antibody concentrations based on empirical testing

• Validation requirements:

  • Confirm specificity using recombinant proteins from the target species

  • Perform knockout/knockdown controls in the new species when possible

  • Consider using orthogonal detection methods to confirm findings

• Cross-reactivity assessment:

  Species	Sequence similarity	Expected reactivity	Recommended dilution	Validation method
  Arabidopsis	100%	Strong	1:1000	Western blot, IP, IHC
  Tomato	Moderate	Variable	1:500	Western blot
  Lettuce	Moderate	Variable	1:500	Western blot
  Other Brassicaceae	High	Likely	1:750	Western blot
  Non-related plants	Low	Unlikely	Test at 1:250	Multiple methods

Systematic testing and optimization are essential when extending antibody applications to new species .

What is the optimal fixation method for preserving At4g35733 epitopes in plant tissues for immunohistochemistry?

Epitope preservation is critical for successful immunohistochemistry with At4g35733 antibodies:

• Fixative selection:

  • 4% paraformaldehyde offers good balance between structure preservation and epitope accessibility

  • Assess alternate fixatives (glutaraldehyde, methanol-acetone) if epitope detection is compromised

  • Consider comparing multiple fixation methods in parallel

• Fixation protocol:

  • Optimize fixation duration (typically 4-24 hours depending on tissue size)

  • Control temperature during fixation (4°C typically reduces over-fixation)

  • Ensure proper tissue penetration through vacuum infiltration for plant tissues

• Antigen retrieval methods:

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

  • Enzymatic retrieval using proteinase K or other proteases

  • Test multiple retrieval methods if initial results are unsatisfactory

• Tissue-specific considerations:

  • Young tissues may require shorter fixation times

  • Lignified tissues might need additional permeabilization steps

  • Highly vacuolated cells may require specialized infiltration approaches

Systematic optimization of these parameters is essential for consistent immunolocalization results .

How can researchers troubleshoot non-specific background in Western blots using At4g35733 antibodies?

Non-specific background in Western blots can obscure true signals. Consider these troubleshooting approaches:

• Sample preparation optimization:

  • Include protease inhibitors to prevent degradation products

  • Optimize protein extraction buffers for plant tissues

  • Consider additional purification steps before electrophoresis

• Blocking optimization:

  • Test different blocking agents (BSA, non-fat milk, commercial blockers)

  • Increase blocking time or blocker concentration

  • Add low concentrations of detergents to reduce hydrophobic interactions

• Antibody dilution and incubation:

  • Titrate primary antibody to determine optimal concentration

  • Extend washing steps after antibody incubations

  • Consider overnight incubations at 4°C rather than shorter incubations at room temperature

• Detection system modifications:

  • Reduce substrate incubation time for enzymatic detection methods

  • Try alternative secondary antibodies

  • Consider fluorescent detection systems which may offer improved signal-to-noise ratios

• Membrane considerations:

  • Ensure complete transfer of proteins to the membrane

  • Consider alternative membrane types (PVDF vs. nitrocellulose)

  • Verify removal of SDS through sufficient washing

Methodical testing of these variables helps identify the specific factors contributing to background issues .

What controls are essential when performing co-immunoprecipitation experiments with At4g35733 antibodies?

Robust co-immunoprecipitation experiments require comprehensive controls:

• Input controls:

  • Total lysate samples to confirm presence of target proteins before IP

  • Quantitative analysis to determine IP efficiency

• Negative controls:

  • IgG control from the same species as the primary antibody

  • IP from knockout/knockdown plant tissues

  • Beads-only control to identify non-specific binding to the matrix

• Reciprocal IPs:

  • Perform IP with antibodies against the suspected interacting partner

  • Confirm interactions in both directions when possible

• Competition controls:

  • Include excess antigen peptide to demonstrate binding specificity

  • Titrate competing peptide to show concentration-dependent effects

• Buffer optimization controls:

  • Test different salt concentrations to distinguish specific from non-specific interactions

  • Evaluate detergent types and concentrations to preserve interactions while reducing background

• Validation controls:

  Control type	Purpose	Expected result
  Input sample	Confirm target presence	Positive signal
  IgG control	Assess non-specific binding	No signal
  Knockout tissue	Verify antibody specificity	No signal
  Peptide competition	Confirm epitope specificity	Reduced/eliminated signal
  Stringency test	Determine interaction strength	Signal decreases with increasing stringency

These controls help discriminate true interactions from experimental artifacts .

How should researchers quantify and normalize At4g35733 protein expression across different developmental stages or stress conditions?

Accurate quantification and normalization are essential for comparative studies:

• Quantification methods:

  • Densitometry analysis of Western blots using appropriate software

  • ELISA-based quantification with standard curves

  • Fluorescence-based quantification with directly labeled antibodies

• Normalization strategies:

  • Use housekeeping proteins appropriate for plant tissues (actin, tubulin, GAPDH)

  • Validate stability of reference proteins under experimental conditions

  • Consider total protein normalization using stain-free technology or Ponceau staining

• Technical considerations:

  • Ensure linear range of detection for both target and reference proteins

  • Include standard curves with recombinant protein when possible

  • Run biological and technical replicates to assess variance

• Advanced approaches:

  • Consider multiple reference proteins and geometric averaging for normalization

  • Implement absolute quantification using purified standards

  • Use spike-in controls for sample-to-sample normalization

• Statistical validation:

  • Apply appropriate statistical tests based on experimental design

  • Perform power analysis to determine adequate sample size

  • Consider normality of data distribution when selecting statistical approaches

This comprehensive approach provides reliable quantification across diverse experimental conditions .

What considerations should guide experimental design when studying protein-protein interactions involving At4g35733?

Studying protein-protein interactions requires careful experimental design:

• Method selection based on interaction characteristics:

  • Co-immunoprecipitation for stable, direct interactions

  • Proximity labeling for transient or weak interactions

  • Split reporter systems for in vivo validation

  • Yeast two-hybrid as a complementary approach

• Control design:

  • Include positive controls with known interacting partners

  • Implement negative controls with proteins not expected to interact

  • Design experiments to distinguish direct vs. indirect interactions

• Validation strategy:

  • Confirm interactions using multiple, orthogonal methods

  • Validate biological relevance through functional assays

  • Consider domain mapping to identify interaction interfaces

• Experimental conditions:

  • Test interactions under native and stress conditions

  • Consider temporal dynamics of interactions during development

  • Evaluate subcellular localization constraints

• Data analysis framework:

  • Establish clear thresholds for defining positive interactions

  • Implement appropriate statistical analysis for replicate experiments

  • Consider network analysis for multiple interaction partners

These considerations help ensure robust, reproducible interaction studies with biological relevance .

How can chromatin immunoprecipitation (ChIP) protocols be optimized for At4g35733 antibodies in plant tissues?

ChIP optimization for plant tissues requires specific adaptations:

• Crosslinking optimization:

  • Test different formaldehyde concentrations (1-3%)

  • Optimize crosslinking time (10-30 minutes) for plant tissues

  • Consider vacuum infiltration to ensure uniform fixation

• Chromatin preparation:

  • Adapt nuclei isolation protocols for plant-specific cell walls

  • Optimize sonication parameters for plant chromatin fragmentation

  • Verify fragment size distribution through gel electrophoresis

• Immunoprecipitation conditions:

  • Determine optimal antibody concentration through titration experiments

  • Test different incubation times and temperatures

  • Consider pre-clearing steps to reduce background

• Washing stringency:

  • Develop appropriate washing protocols to balance signal retention and background reduction

  • Include controls with increasing washing stringency to optimize signal-to-noise ratio

• DNA recovery and analysis:

  • Compare different DNA purification methods for yield and purity

  • Implement appropriate controls for qPCR analysis

  • Consider sequencing depth requirements for ChIP-seq applications

• Plant-specific considerations:

  • Account for endogenous plant compounds that may interfere with immunoprecipitation

  • Consider tissue-specific optimization due to varying chromatin accessibility

  • Adapt protocols for different developmental stages or stress conditions

These optimizations help overcome the unique challenges of plant ChIP experiments .

What experimental approaches can distinguish between specific and non-specific binding when new At4g35733 antibodies are being characterized?

Rigorous characterization of antibody specificity requires multiple approaches:

• Genetic validation:

  • Test antibodies on knockout/knockdown plant lines

  • Use overexpression lines to confirm signal increase

  • Compare multiple independent mutant alleles when available

• Biochemical validation:

  • Perform peptide competition assays with the immunizing antigen

  • Test cross-reactivity with related proteins through Western blotting

  • Use recombinant protein arrays to assess broader specificity

• Analytical approaches:

  • Perform immunoprecipitation followed by mass spectrometry

  • Compare results across multiple antibody lots

  • Evaluate consistency across different applications (Western, IP, IHC)

• Systematic validation series:

  Validation approach	Purpose	Interpretation
  Knockout tissue testing	Confirm specificity	Loss of signal indicates specificity
  Overexpression testing	Verify target detection	Increased signal confirms detection
  Peptide competition	Identify epitope specificity	Dose-dependent signal reduction
  IP-MS	Identify all targets	Single major hit indicates specificity
  Cross-reactivity panel	Assess related protein binding	Minimal binding to non-targets

These approaches provide a comprehensive assessment of antibody specificity and suitability for specific applications .

How should researchers interpret contradictory results from different antibody-based detection methods for At4g35733?

Contradictory results require systematic troubleshooting and interpretation:

• Method-specific considerations:

  • Evaluate whether techniques detect native vs. denatured proteins

  • Consider epitope accessibility differences between methods

  • Assess whether methods detect different pools of the protein (membrane-bound vs. soluble)

• Analytical approach:

  • Compare antibodies targeting different epitopes of At4g35733

  • Correlate protein detection with mRNA expression data

  • Implement orthogonal, non-antibody-based detection methods

• Technical validation:

  • Review all positive and negative controls for each method

  • Assess reagent quality and experimental conditions

  • Consider biological variability in the samples being analyzed

• Biological interpretation:

  • Evaluate whether contradictions reflect actual biological complexity

  • Consider post-translational modifications affecting epitope recognition

  • Assess potential protein interactions masking epitopes

• Resolution strategy:

  • Design decisive experiments that can explain the contradictions

  • Implement multiple detection methods in parallel

  • Consider developing new reagents if existing ones prove inadequate

What statistical approaches are appropriate for analyzing semi-quantitative immunoblot data for At4g35733 across multiple experimental conditions?

• Data acquisition considerations:

  • Ensure linearity of detection system within the analyzed range

  • Include technical and biological replicates

  • Control for loading variation through appropriate normalization

• Normalization approaches:

  • Ratio to housekeeping proteins (validated for stability under experimental conditions)

  • Total protein normalization (Ponceau S, stain-free technology)

  • Spiked internal standards for absolute quantification

• Statistical methods:

  • For normally distributed data: ANOVA with appropriate post-hoc tests

  • For non-parametric data: Kruskal-Wallis or similar approaches

  • For time-series data: repeated measures ANOVA or mixed-effects models

• Advanced considerations:

  • Power analysis to determine adequate sample size

  • Multiple testing correction for complex experimental designs

  • Consideration of experimental batch effects

• Presentation guidelines:

  • Include measures of variance (standard deviation or standard error)

  • Present individual data points alongside means/medians

  • Clearly indicate statistical significance and test methods

These approaches ensure robust analysis of semi-quantitative data from immunoblot experiments .

What are the most common causes of inconsistent results when using At4g35733 antibodies, and how can they be systematically addressed?

Inconsistent results can be addressed through systematic troubleshooting:

• Antibody variables:

  • Lot-to-lot variation in commercial antibodies

  • Antibody degradation due to improper storage

  • Inconsistent antibody dilutions or incubation conditions

• Sample preparation factors:

  • Variations in protein extraction efficiency

  • Inconsistent sample handling affecting protein integrity

  • Buffer composition changes affecting epitope accessibility

• Technical considerations:

  • Variations in transfer efficiency for Western blots

  • Inconsistent blocking effectiveness

  • Detection system variability

• Biological variables:

  • Growth condition variations affecting protein expression

  • Developmental stage differences between experiments

  • Circadian or diurnal regulation of target protein

• Systematic resolution approach:

  Issue	Diagnostic approach	Solution strategy
  Antibody degradation	Test new vs. old aliquots	Prepare fresh aliquots, verify storage
  Protocol inconsistency	Document all steps precisely	Implement detailed SOPs
  Sample variation	Compare extraction methods	Standardize sample preparation
  Technical variation	Include internal controls	Implement quality control checkpoints
  Biological variation	Monitor growth conditions	Synchronize plant material carefully

This systematic approach helps identify and address sources of variability .

How can researchers determine the optimal antibody concentration for each application when working with At4g35733 antibodies?

Determining optimal antibody concentration requires empirical testing:

• Titration experiments:

  • Test a wide concentration range (typically 1:100 to 1:10,000 dilutions)

  • Evaluate signal-to-noise ratio at each concentration

  • Include positive and negative controls at each concentration

• Application-specific considerations:

  • Western blotting typically requires lower antibody concentrations than immunohistochemistry

  • ELISA may require different optimal concentrations than immunoprecipitation

  • Flow cytometry applications may require higher concentrations than Western blotting

• Optimization strategy:

  • Start with manufacturer's recommended dilution (if available)

  • Perform initial broad-range titration

  • Refine with narrow-range titration around promising concentrations

• Evaluation criteria:

  • Signal intensity at expected molecular weight/location

  • Background level and non-specific binding

  • Consistency across replicates

  • Cost-effectiveness of antibody usage

• Documentation and standardization:

  • Record optimal concentrations for each application

  • Document lot numbers and potential variation between lots

  • Establish standard curves for quantitative applications

This methodical approach ensures optimal antibody performance while minimizing reagent usage .

How can At4g35733 antibodies be adapted for high-throughput or automated plant phenotyping applications?

Adapting antibodies for high-throughput applications requires specific considerations:

• Assay miniaturization:

  • Develop microplate-based ELISA protocols

  • Optimize dot blot or slot blot approaches for rapid screening

  • Implement automated Western blot systems with standardized protocols

• Automation compatibility:

  • Standardize all reagents for robot handling

  • Develop protocols with minimal manual intervention steps

  • Validate reproducibility across automated runs

• Data acquisition systems:

  • Implement automated imaging systems with standardized settings

  • Develop image analysis algorithms for consistent quantification

  • Establish quality control metrics for automated data processing

• Throughput enhancements:

  • Multiplex detection with antibodies against multiple targets

  • Develop tissue microarrays for simultaneous analysis of multiple samples

  • Implement batch processing protocols with appropriate controls

• Validation and quality control:

  • Include standard samples across plates/batches

  • Implement automated outlier detection

  • Develop statistical approaches for large dataset analysis

These adaptations enable scaling antibody-based assays for large studies while maintaining data quality .

What emerging technologies might complement or replace traditional antibody-based detection of At4g35733 in the next five years?

Several emerging technologies show promise for protein detection:

• Aptamer-based approaches:

  • DNA/RNA aptamers selected for specific protein binding

  • Advantages include synthetic production and stability

  • Applications in biosensors and affinity purification

• Nanobody technology:

  • Single-domain antibody fragments derived from camelid antibodies

  • Smaller size enables access to restricted epitopes

  • Enhanced stability and recombinant production

• CRISPR-based protein detection:

  • Cas13-based detection systems adapted for protein targets

  • Potential for enhanced sensitivity through nucleic acid amplification

  • Multiplexed detection capabilities

• Mass spectrometry advances:

  • Targeted proteomics with increasing sensitivity

  • Label-free quantification improvements

  • Simplified sample preparation workflows

• Proximity labeling technologies:

  • BioID, APEX, and related approaches for in vivo protein detection

  • Spatial and temporal resolution of protein localization

  • Ability to detect weak or transient interactions

These technologies offer complementary approaches to traditional antibody methods, potentially addressing current limitations in specificity, throughput, and quantification .