The ERECTA-family receptor-like kinase, ERL1, plays a crucial role in regulating plant development. Specifically, it influences inflorescence architecture, organ shape, and stomatal patterning, including stomatal density and clustering. ERL1 functions in concert with other ERECTA family members (ER and ERL2) and is involved in procambial development. Importantly, ERL1 forms a functional ligand-receptor pair with EPF1 (Accession Q8S8I4) and constitutes a complex with TMM, facilitating the recognition of stomatal regulatory peptides EPF1, EPF2, and EPFL9/STOMAGEN.
Further Research: The ERECTA family of leucine-rich repeat receptor-like kinases (ER, ERL1, ERL2) collectively govern stomatal patterning. Individual members within this family exhibit specific roles in regulating stomatal stem cell fate and guard cell differentiation. (See reference below for details on ERL1's specific contribution).
ERL1 is a major receptor restricting plant stomatal differentiation that undergoes dynamic subcellular behaviors in response to different EPIDERMAL PATTERNING FACTOR (EPF) peptides . It plays dual functions in regulating guard cell differentiation both autocrinally and by enforcing stomatal spacing of neighboring cells paracrinally . Antibodies targeting ERL1 are essential tools for studying receptor localization, trafficking dynamics, and signaling mechanisms in plant development research.
Based on research methodologies used with similar receptor antibodies, ERL1 antibodies are applicable for:
Immunofluorescence microscopy for subcellular localization studies
Western blotting for protein expression analysis
Immunoprecipitation for protein-protein interaction studies
Co-localization studies with organelle markers
Tracking receptor dynamics in response to different ligands
When selecting antibodies for these applications, researchers should consider specificity, detection sensitivity, and validated applications in similar experimental contexts.
This is a critical consideration as ERL1 shares sequence homology with other ERECTA family members. Effective approaches include:
Using antibodies targeting unique epitopes in the ERL1 sequence not shared with ERECTA or ERL2
Validating specificity using erl1 knockout plants as negative controls
Performing peptide competition assays to confirm antibody specificity
Cross-validation with fluorescently tagged ERL1 protein expression patterns
Research shows that ERL1 undergoes differential endocytic trafficking depending on the activating peptide . When designing experiments to study this:
Use dual-labeling approaches with antibodies targeting different ERL1 epitopes
Combine with markers for endocytic compartments (early endosomes, MVB/LE, vacuoles)
Design time-course experiments to capture transitional states
Consider treatment with endocytosis inhibitors like Tyrphostin A23 (Tyr A23) as controls
The table below summarizes ERL1 trafficking responses to different peptides:
Contradictory localization data often stems from methodological differences. Consider:
Fixation artifacts: Compare results from formaldehyde fixation (as used in standard protocols ) with cryo-fixation methods
Epitope masking: Test multiple antibodies targeting different regions of ERL1
Trafficking dynamics: Conduct pulse-chase experiments to distinguish steady-state from dynamic populations
Signaling state differences: Standardize pre-experimental conditions to control ERL1 activation state
Cell-type variation: Account for differential expression and function of ERL1 in different cell types
This critical distinction requires careful experimental design:
Control experiments with inactive ligand analogs
Quantitative comparison with baseline internalization rates
Use of Brefeldin A (BFA) to trap constitutively internalized receptors in BFA bodies
Analysis of co-receptor requirements (e.g., TMM dependence for EPF1-induced but not constitutive internalization)
Pharmacological inhibition with endocytosis blockers such as Endosidin 9-17
Based on established protocols for receptor proteins in plant tissues , an optimized protocol would include:
Fixation: 4% pH neutral buffered formaldehyde for 15 minutes
Permeabilization: 0.2% Triton X-100/1% BSA/PBS solution for 20 minutes at room temperature
Blocking: 1% BSA in PBS for 30-60 minutes
Primary antibody incubation: One hour in a humidified environment at room temperature
Secondary antibody: Fluorophore-conjugated antibodies (e.g., ATTO-555 or ATTO-633) at 1:200 dilution
Counterstaining: DAPI for nuclear visualization
Mounting: Anti-fade mounting medium to preserve fluorescence
For co-localization studies, combining mouse and rabbit monoclonal antibodies allows simultaneous detection of multiple targets .
For successful western blotting:
Sample preparation: Use buffer containing phosphatase inhibitors to preserve phosphorylation states
Protein extraction: Optimize membrane protein extraction methods as ERL1 is a transmembrane receptor
Gel concentration: 8-10% SDS-PAGE gels are typically suitable for receptor proteins
Transfer conditions: Semi-dry or wet transfer optimized for membrane proteins
Blocking: 5% non-fat milk or BSA depending on the antibody specifications
Antibody dilution: Optimize through titration experiments (typical range 1:500-1:2000)
Detection system: Consider enhanced chemiluminescence or fluorescent secondary antibodies
Based on endocytosis research methodologies , essential controls include:
Genetic controls: erl1 knockout mutants and TMM mutants to assess co-receptor requirements
Trafficking markers: Endocytic tracer dye FM4-64 to visualize membrane trafficking pathways
Pharmacological treatments:
Organelle co-localization with established markers:
Variability in staining patterns can result from:
Technical factors:
Inconsistent fixation duration or formaldehyde concentration
Variable permeabilization efficiency across tissue types
Antibody batch variation
Inconsistent washing steps
Biological factors:
ERL1 conformational changes upon ligand binding
Developmental stage differences affecting ERL1 expression
Rapid receptor turnover rates in response to stimuli
Epitope masking due to protein-protein interactions
High background is a common challenge. Effective solutions include:
Increase blocking stringency by using combination blockers (BSA + normal serum)
Optimize antibody concentration through careful titration experiments
Extend washing duration and increase detergent concentration in wash buffers
Pre-absorb secondary antibodies with plant tissue extract
Include peptide competition controls to distinguish specific from non-specific signals
For plant tissues, include treatments to reduce autofluorescence (e.g., 0.1% Sudan Black B)
When reconciling differences between antibody staining and fluorescent protein data:
Consider epitope accessibility: Antibodies may not access all ERL1 populations
Assess fixation effects: Compare live-cell imaging with fixed-cell immunofluorescence
Evaluate overexpression artifacts: Compare native ERL1 levels with transgenic expression
Analyze tag interference: Fluorescent protein tags may alter trafficking dynamics
Implement proximity ligation assays (PLA) as an alternative approach to validate interactions
For rigorous quantification of ERL1 localization:
Fluorescence intensity ratio: Measure plasma membrane-to-intracellular signal ratio
Co-localization analysis: Calculate Pearson's or Manders' coefficients with compartment markers
Object-based analysis: Count distinct ERL1-positive vesicles and measure their size distribution
Kinetic analysis: Track intensity changes over time following ligand application
Distribution profiling: Generate intensity line profiles across cells or tissues
The experimental approach should be tailored to the specific research question:
Detecting conformational changes requires specialized approaches:
Use conformation-sensitive antibodies that recognize specific activation states
Compare accessibility of different epitopes in activated versus inactive receptors
Implement Förster resonance energy transfer (FRET) between different antibody-conjugated fluorophores
Correlate with functional readouts of receptor activation (e.g., downstream signaling)
Combine with proximity ligation assays to detect changes in protein-protein interactions
For robust statistical analysis of trafficking data:
For comparing treatments: ANOVA with appropriate post-hoc tests
For time course experiments: Repeated measures ANOVA or mixed-effects modeling
For co-localization analysis: Fisher's z-transformation of correlation coefficients before comparison
For heterogeneous cell populations: Consider hierarchical clustering to identify response patterns
For complex datasets: Consider principal component analysis to identify key variables driving differences
When reporting results, include both representative images and quantitative data with appropriate statistical tests to demonstrate significance of observed differences.