At2g35130 Antibody

What is At2g35130 and why is it significant in plant research?

At2g35130 is a Tetratricopeptide repeat (TPR)-like superfamily protein in Arabidopsis thaliana that has been identified in studies investigating cell wall matrix polysaccharides. It is localized in the endomembrane system and was specifically identified using the LM15 antibody with glycan-protein (GP) cross-linkers in proximity cross-linking immunoprecipitation studies . The protein's association with xyloglucan (recognized by LM15 antibody) suggests potential involvement in cell wall biosynthesis or remodeling processes. Understanding At2g35130's function contributes to our knowledge of plant cell wall dynamics, which is crucial for numerous aspects of plant growth, development, and response to environmental stresses.

What cellular functions are associated with At2g35130?

At2g35130, as a tetratricopeptide repeat-containing protein, likely functions in protein-protein interactions, as TPR domains are known to mediate such interactions. In the context of cell wall biology, At2g35130 may participate in protein complexes involved in polysaccharide synthesis, modification, or transport. Its localization in the endomembrane system (ES) suggests involvement in secretory pathways responsible for delivering cell wall components to the plasma membrane and extracellular space . The protein was identified in cross-linking studies with xyloglucan-binding antibodies, indicating potential roles in xyloglucan processing or deposition within the cell wall matrix.

What detection methods are most effective for At2g35130 in plant tissues?

For effective detection of At2g35130 in plant tissues, researchers should consider several complementary approaches:

• Western blotting: Effective for protein quantification and size verification

• Immunoprecipitation: Particularly valuable when combined with proximity cross-linking

• Immunolocalization: For visualizing subcellular distribution

• Mass spectrometry: For confirmation of protein identity and post-translational modifications

Based on published research, proximity cross-linking combined with immunoprecipitation has proven effective for At2g35130 detection, especially using glycan-protein (GP) cross-linkers that preserve interactions between At2g35130 and cell wall polysaccharides . When designing experiments, researchers should include appropriate controls such as samples from knockout/knockdown plants and pre-immune serum controls to confirm antibody specificity.

How can I validate the specificity of an At2g35130 antibody for my research?

Validating the specificity of an At2g35130 antibody should follow the five pillars of antibody validation as outlined in contemporary research :

• Orthogonal strategy: Compare antibody-based results with antibody-independent methods such as RNA-seq or proteomics. For At2g35130, correlate protein detection by the antibody with mRNA expression levels or mass spectrometry data.

• Genetic strategy: Test the antibody in samples with genetically modified At2g35130 expression:

  • Use T-DNA insertion lines or CRISPR-modified plants lacking At2g35130

  • Apply siRNA knockdown showing at least 25% reduction in target protein

  • Compare signal intensity between wild-type and modified samples to confirm specificity

• Recombinant expression strategy: Overexpress At2g35130 in a system with minimal endogenous expression (such as HEK 293 cells as described in research methodologies) and confirm increased antibody signal .

• Independent antibody strategy: Compare results using two different antibodies targeting distinct epitopes of At2g35130.

• Capture mass spectrometry strategy: Perform immunoprecipitation with the At2g35130 antibody followed by mass spectrometry to confirm the antibody captures the intended protein.

These validation approaches should be tailored to your specific application (Western blot, immunoprecipitation, or immunolocalization).

How does the tetratricopeptide repeat structure of At2g35130 affect antibody design and specificity?

The tetratricopeptide repeat (TPR) structure of At2g35130 significantly impacts antibody design and specificity:

• Structural considerations: TPR domains consist of repeating helix-turn-helix motifs that form a superhelical structure. This repetitive nature means that:

  • Epitopes within the TPR region may be present multiple times within the protein

  • Similar motifs exist in other TPR-containing proteins across species, increasing cross-reactivity risks

  • The three-dimensional folding creates complex conformational epitopes

• Epitope selection strategies:

  • Target unique regions outside the TPR domain whenever possible

  • If targeting within TPR regions, focus on less conserved residues that distinguish At2g35130 from other TPR proteins

  • Consider using computational epitope prediction tools that account for both uniqueness and accessibility

• Antibody format considerations:

  • Monoclonal antibodies may provide higher specificity for unique epitopes

  • Polyclonal antibodies offer broader recognition but higher cross-reactivity risk with other TPR proteins

  • Recombinant antibody fragments may access epitopes in folded TPR structures more effectively

• Validation requirements:

  • Essential to test for cross-reactivity with other TPR-containing proteins

  • Critical to include TPR protein-rich negative controls in validation experiments

  • Important to verify specificity in the experimental system where the antibody will be used

At2g35130 is listed as a "Tetratricopeptide repeat (TPR)-like superfamily protein" in research databases, emphasizing the importance of these structural considerations when designing and validating antibodies against this target .

What are the optimal cross-linking protocols for studying At2g35130 interactions with cell wall components?

Based on published research data, the following cross-linking protocols have proven effective for studying At2g35130 interactions with cell wall components:

• Cross-linker selection:

  • Glycan-protein (GP) cross-linkers: Most effective for capturing At2g35130, as demonstrated in studies where it was identified with the LM15 antibody

  • Protein-protein (PP) cross-linkers: For capturing protein-protein interactions

  • Combined GP+PP approach: For comprehensive interaction network mapping

• Experimental procedure:

  Step	Protocol Details	Notes
  Sample preparation	Fresh Arabidopsis seedlings or tissues	Use tissue with active cell wall synthesis
  Cross-linker application	Apply GP cross-linkers (e.g., glycoside-phenylazide derivatives)	Optimal concentration determined empirically
  UV activation	Expose samples to UV light (365 nm)	Duration: typically 10-30 minutes
  Tissue homogenization	Extract in buffer with protease inhibitors	Maintain cold temperature
  Immunoprecipitation	Use At2g35130 antibody with protein A/G beads	Include non-immune serum control
  Elution	Elute under denaturing conditions	SDS buffer with heating
  Analysis	Western blot or mass spectrometry	MS identifies interaction partners

• Optimization considerations:

  • Cross-linker concentration: Test range from 0.5-5 mM

  • Cross-linking time: Balance between sufficient linkage and excessive background

  • Extraction conditions: Adjust detergent types/concentrations to solubilize membrane proteins while preserving interactions

• Controls:

  • No cross-linker control

  • Non-specific antibody immunoprecipitation

  • Competition with excess antigen

  • At2g35130 knockout/knockdown samples

Research has shown that GP cross-linkers were particularly effective for capturing At2g35130 with the LM15 antibody, identifying it in a complex with xyloglucan components of the cell wall .

How can I distinguish between specific and non-specific binding when using At2g35130 antibodies?

Distinguishing between specific and non-specific binding when using At2g35130 antibodies requires a systematic approach:

• Essential controls for validation:

  • Genetic controls: Test antibody in At2g35130 knockout or knockdown plants

  • Peptide competition: Pre-incubate antibody with immunizing peptide

  • Secondary antibody-only: Omit primary antibody to assess secondary antibody non-specific binding

  • Isotype control: Use non-specific antibody of same isotype/species

  • Pre-immune serum: For polyclonal antibodies

• Biochemical validation approaches:

  • Western blot validation: Confirm single band of correct molecular weight

  • Immunoprecipitation-mass spectrometry: Verify At2g35130 is captured

  • Orthogonal method correlation: Compare antibody detection with mRNA expression

• Signal characteristics analysis:

  Specific Signal	Non-specific Signal
  Consistent molecular weight	Variable or multiple unexpected bands
  Reduced/absent in knockout samples	Present in knockout samples
  Blocked by immunizing peptide	Unaffected by immunizing peptide
  Correlates with mRNA expression	Does not correlate with transcript levels
  Reproducible across experiments	Variable between experiments
  Expected subcellular localization	Diffuse or inconsistent localization

• Advanced validation strategies:

  • Use multiple antibodies targeting different epitopes of At2g35130

  • Apply recombinant expression system with controlled expression

  • Perform quantitative analysis comparing signal in different samples with expected expression patterns

• Tissue-specific considerations:

  • Plant tissues often show high autofluorescence - use appropriate controls

  • Cell wall components can cause high background - optimize blocking

  • Endomembrane localization of At2g35130 may require specific permeabilization protocols

Implementing these approaches will significantly increase confidence in the specificity of observed signals when using At2g35130 antibodies .

What sample preparation methods maximize At2g35130 antibody detection in plant tissues?

Optimal sample preparation methods for At2g35130 antibody detection in plant tissues should address its endomembrane localization and potential association with cell wall components:

• Tissue extraction protocols:

  Application	Recommended Buffer	Additives	Notes
  Western blot	50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% Triton X-100	Protease inhibitors, 1 mM EDTA	Add 0.5% sodium deoxycholate for membrane proteins
  Immunoprecipitation	50 mM HEPES pH 7.5, 150 mM NaCl, 0.5% NP-40	Protease inhibitors, 10% glycerol	Gentler detergent to preserve interactions
  Immunolocalization	4% paraformaldehyde in PBS	None	Alternative: 0.25% glutaraldehyde + 1.5% paraformaldehyde

• Critical steps for endomembrane proteins:

  • Membrane solubilization: Use detergents appropriate for endomembrane proteins (Triton X-100, digitonin, or CHAPS)

  • Protein denaturation: For Western blots, heat samples at 70°C instead of 95°C to prevent aggregation

  • Reducing agents: Include fresh DTT (5 mM) or β-mercaptoethanol to maintain epitope accessibility

• Cell wall considerations:

  • If studying At2g35130's association with cell wall components, consider:

    • Cross-linking prior to extraction (as detailed in FAQ 2.3)

    • Sequential extraction protocols to distinguish between different subcellular pools

    • Enzymatic treatments (cellulase, pectinase) to release wall-associated proteins

• Immunolocalization-specific considerations:

  • Fixation: 4% paraformaldehyde (10-30 minutes)

  • Permeabilization: 0.1-0.3% Triton X-100 or 0.05-0.1% saponin

  • Antigen retrieval: Mild heat treatment (85-95°C) in citrate buffer (pH 6.0)

  • Blocking: 3-5% BSA or normal serum with 1-3% non-fat dry milk to reduce plant-specific background

• Preservation of protein interactions:

  • For in vivo interaction studies, cross-linking has proven effective for At2g35130, particularly using glycan-protein (GP) cross-linkers as demonstrated in published research

  • Maintain colder temperatures throughout extraction to minimize protein degradation

  • Include phosphatase inhibitors to preserve post-translational modifications

These protocols should be optimized for specific plant tissues and experimental conditions.

How should I design controls for At2g35130 immunoprecipitation experiments?

Designing robust controls for At2g35130 immunoprecipitation experiments is critical for distinguishing genuine interactions from background:

• Essential experimental controls:

  Control Type	Description	Purpose
  Input sample	5-10% of pre-IP lysate	Confirms target protein presence in starting material
  No-antibody	Beads only, no antibody	Identifies proteins binding non-specifically to beads
  Isotype control	Non-specific antibody of same isotype	Identifies proteins binding to antibody framework
  Pre-immune serum	For polyclonal antibodies	Controls for non-specific serum components
  Knockout/Knockdown	Samples lacking At2g35130	Gold standard for specificity verification
  Competitive elution	Addition of excess antigen	Confirms specific binding to antibody

• Processing controls:

  • Technical replicates: Process multiple samples in parallel to assess reproducibility

  • Bead type comparison: Compare results using different affinity matrices (Protein A/G, magnetic vs. agarose)

  • Crosslinking controls: Compare crosslinked vs. non-crosslinked samples

  • Wash stringency gradient: Analyze samples with increasing wash stringency

• Analysis validation approaches:

  • Reverse immunoprecipitation: Use antibodies against potential interaction partners to confirm association

  • Proximity labeling validation: Confirm interactions using orthogonal methods like BioID or APEX

  • Native vs. denaturing conditions: Compare interaction profiles under different conditions

• At2g35130-specific considerations:

  • Include controls specific to endomembrane proteins and cell wall components

  • As shown in research, compare results using different cross-linkers (GP, PP, and GP+PP)

  • Consider including antibodies against related TPR proteins to assess cross-reactivity

• Data analysis controls:

  • Apply statistical filters to distinguish significant interactions from background

  • Compare identified proteins against the CRAPome database of common contaminants

  • Implement quantitative approaches like SAINT or CompPASS for scoring interactions

Properly designed controls are essential for generating reliable interaction data, particularly for proteins like At2g35130 that may function in complex with both proteins and polysaccharides in the endomembrane system .

What strategies can improve reproducibility when using At2g35130 antibodies across different plant species?

Improving reproducibility when using At2g35130 antibodies across different plant species requires addressing several challenges:

• Sequence conservation assessment:

  • Perform multiple sequence alignment of At2g35130 homologs across target species

  • Identify conserved and variable regions that might affect antibody binding

  • Select antibodies targeting highly conserved epitopes for cross-species applications

• Epitope-focused validation pipeline:

  Step	Method	Purpose
  Bioinformatic analysis	Sequence alignment, epitope mapping	Predict cross-reactivity potential
  Western blot	Protein extracts from multiple species	Confirm binding to proteins of expected size
  Immunoprecipitation	Pull-down followed by mass spectrometry	Verify correct target protein capture
  Immunolocalization	Compare localization patterns	Confirm consistent subcellular distribution

• Optimization parameters for cross-species applications:

  • Antibody concentration: Typically requires titration for each species

  • Incubation conditions: May need longer incubation times for less conserved targets

  • Buffer compositions: Adjust salt and detergent concentrations for different tissues

  • Blocking reagents: Test species-specific blockers to reduce background

• Technical standardization approaches:

  • Standardize tissue collection, age, and growth conditions

  • Use consistent sample preparation protocols across species

  • Prepare and store antibody aliquots to minimize freeze-thaw cycles

  • Develop detailed SOPs for each procedure to ensure consistency

• Controls for cross-species applications:

  • Include recombinant protein controls when possible

  • Use tissue from gene knockout/knockdown plants when available

  • Consider synthetic peptide controls matching the target epitope

  • Include gradient experiments showing detection limits in each species

• TPR domain-specific considerations:

  • TPR domains like those in At2g35130 are structurally conserved but may have sequence variations

  • Choose antibodies targeting unique regions outside the TPR repeats for higher specificity

  • Consider the use of domain-specific antibodies when studying conserved functions

• Documentation and reporting:

  • Maintain detailed records of all optimization experiments

  • Report all experimental conditions in publications

  • Share protocols through repositories to improve community-wide reproducibility

These strategies will help overcome the challenges of using At2g35130 antibodies across different plant species, improving reproducibility and confidence in research findings.

How should I analyze and interpret At2g35130 protein interaction networks?

Analyzing and interpreting At2g35130 protein interaction networks requires a systematic approach:

• Data filtering and quality control:

  • Remove common contaminants using established databases

  • Apply statistical thresholds to distinguish specific from non-specific interactions

  • Categorize interactions based on detection frequency and abundance

• Network analysis framework:

  Analysis Type	Methods	Output
  Primary network	Direct interactors from IP-MS	Core interaction partners
  Extended network	Integration with database interactions	Functional context
  Network metrics	Centrality, clustering, path analysis	Network architecture
  Functional enrichment	GO terms, pathway analysis	Biological roles

• At2g35130-specific interaction interpretation:
  Research data shows that At2g35130 interactors can be classified into several functional categories :

  • Cell wall biosynthesis enzymes (especially xyloglucan-related)

  • Membrane trafficking components

  • Signaling proteins

  • Structural proteins

• Integration with protein interaction databases:
  Based on research findings, utilize:

  • DeepAraPPI (deep learning-assisted prediction)

  • AtMAD (experimental data-based)

  The data indicates that 19 and 24 out of 63 identified proteins associated with cell wall polysaccharides matched with DeepAraPPI and AtMAD databases, respectively .

• Network visualization strategies:

  • Organize by subcellular localization

  • Color-code by functional category

  • Represent interaction confidence through edge thickness

  • Highlight interactions validated by multiple methods

• Biological context interpretation:

  • Map interactions to known cellular pathways

  • Identify potential protein complexes through clustering

  • Analyze co-expression patterns across tissues/conditions

  • Consider evolutionary conservation of interactions

• Validation prioritization:

  • Rank novel interactions for experimental validation

  • Prioritize interactions with proteins of complementary function

  • Focus on interactions consistent with At2g35130's endomembrane localization

  • Consider proximity to known cell wall-related proteins

Research has shown that At2g35130 interacts with proteins involved in cell wall matrix polysaccharide synthesis and modification, consistent with its identification using the LM15 antibody (which recognizes xyloglucan) .

How can I integrate At2g35130 antibody data with other omics approaches?

Integrating At2g35130 antibody data with other omics approaches provides a comprehensive understanding of this protein's function:

• Multi-omics integration framework:

  Omics Layer	Technology	Integration with Antibody Data
  Genomics	Whole genome sequencing, GWAS	Link genetic variants to protein abundance/modification
  Transcriptomics	RNA-seq, microarray	Correlate protein levels with mRNA expression
  Proteomics	Mass spectrometry	Validate antibody specificity, identify modifications
  Metabolomics	LC-MS, GC-MS	Connect At2g35130 function to metabolic outcomes
  Phenomics	High-throughput phenotyping	Associate protein levels with plant phenotypes

• Data correlation approaches:

  • Calculate Pearson/Spearman correlations between antibody-based quantification and other data types

  • Perform principal component analysis to identify patterns across omics layers

  • Apply machine learning methods to identify predictive features

• Biological network integration:

  • Map antibody-detected interactions to transcriptional networks

  • Overlay protein-protein interactions with genetic interaction maps

  • Connect protein abundance with metabolic pathway activities

• Workflow for At2g35130 multi-omics analysis:
  a) Antibody-based proteomics:

  • Western blot quantification across conditions/tissues

  • Immunoprecipitation followed by mass spectrometry

  • Proximity labeling to identify interaction neighborhood

  b) Complementary omics:

  • Transcriptomics in matching samples

  • Phosphoproteomics to identify post-translational modifications

  • Cell wall composition analysis (particularly xyloglucan content)

  c) Integration analysis:

  • Identify concordant and discordant patterns

  • Develop predictive models of At2g35130 function

  • Generate testable hypotheses about mechanism

• Visualization strategies:

  • Multi-omics heatmaps showing patterns across data types

  • Network diagrams integrating different interaction types

  • Pathway maps highlighting regulation at multiple levels

• At2g35130-specific integration insights:
  Research suggests integration priorities should focus on:

  • Cell wall polysaccharide composition (particularly xyloglucan)

  • Endomembrane system dynamics

  • Protein interaction networks, especially those identified using glycan-protein cross-linkers

• Statistical considerations:

  • Account for different noise levels across platforms

  • Apply appropriate normalization for cross-platform comparison

  • Consider Bayesian approaches for data integration with prior knowledge

Effective integration of At2g35130 antibody data with other omics approaches will provide a systems-level understanding of this protein's function in cell wall biology and plant development.

What are the current limitations and future directions for At2g35130 antibody research?

Current limitations in At2g35130 antibody research include challenges with specificity validation, limited commercial availability, and incomplete characterization across developmental stages and stress conditions. The tetratricopeptide repeat structure poses particular challenges for antibody specificity due to structural similarity with other TPR proteins.

Future directions should focus on developing comprehensively validated antibodies suitable for diverse applications, expanding functional studies using these antibodies, and integrating antibody-based approaches with emerging technologies. Cross-linking immunoprecipitation methods have proven valuable for studying At2g35130's associations with cell wall components and should be further refined .

Additionally, researchers should explore the protein's interactions with cell wall polysaccharides in greater detail, particularly its relationship with xyloglucan (detected by the LM15 antibody) and other cell wall components. The development of antibodies recognizing specific post-translational modifications of At2g35130 could provide valuable insights into its regulation and function.

The five-pillar approach to antibody validation (orthogonal, genetic, recombinant expression, independent antibody, and capture mass spectrometry strategies) represents the gold standard for future At2g35130 antibody development and validation . Applying these rigorous validation methods will enhance reproducibility and reliability in plant cell wall research involving this important protein.

How can researchers contribute to improving At2g35130 antibody resources?

Researchers can contribute to improving At2g35130 antibody resources through:

• Comprehensive validation and reporting:

  • Validate antibodies using multiple approaches (the five pillars)

  • Report detailed validation protocols and results

  • Share both positive and negative results to help the community

• Resource development and sharing:

  • Deposit validated antibodies in repositories

  • Share detailed protocols for optimal use

  • Contribute to community standards for validation

• Application expansion:

  • Develop optimized protocols for diverse applications

  • Test antibodies across different plant species

  • Validate for emerging techniques (super-resolution microscopy, spatial proteomics)

• Collaborative initiatives:

  • Participate in antibody validation consortia

  • Engage in round-robin testing across laboratories

  • Contribute to database resources for plant antibodies