LRCH3 Antibody

What is LRCH3 protein and what are its key characteristics?

LRCH3 is a protein characterized by leucine-rich repeats and calponin homology (CH) domains. The full name is leucine-rich repeats and calponin homology domain containing 3 . It has a calculated molecular weight of 86 kDa, though it typically appears at approximately 70 kDa in experimental conditions like Western blotting . The gene is identified by NCBI Gene ID 84859 and corresponds to UniProt ID Q96II8 . The protein's structural characteristics suggest potential roles in protein-protein interactions and possibly cytoskeletal organization, though its precise biological functions remain under investigation.

What experimental applications have been validated for LRCH3 antibodies?

LRCH3 antibodies have been validated for multiple experimental applications as detailed in the table below:

These validations provide researchers with reliable parameters for experimental design when studying LRCH3 across different biological contexts.

What species reactivity has been confirmed for commercial LRCH3 antibodies?

Commercial LRCH3 antibodies have demonstrated cross-reactivity with samples from multiple species. Currently validated reactivity includes human, mouse, and rat samples . This multi-species reactivity makes these antibodies particularly valuable for comparative studies across different mammalian models. When planning to use these antibodies with samples from other species, researchers should conduct preliminary validation experiments to confirm cross-reactivity due to potential sequence variations that might affect antibody binding.

What are the optimal Western blot protocols for LRCH3 detection?

For optimal Western blot detection of LRCH3, researchers should consider the following protocol guidelines:

• Sample preparation: Effectively lyse cells or tissues using RIPA or similar buffers containing protease inhibitors to prevent degradation.

• Protein separation: Use 8-12% SDS-PAGE gels, which provide optimal resolution for the 70 kDa LRCH3 protein.

• Transfer conditions: For proteins in this molecular weight range, semi-dry or wet transfer systems work effectively, with PVDF membranes often providing better protein retention than nitrocellulose.

• Antibody incubation: Dilute LRCH3 antibody at 1:500-1:2400 depending on the specific product and experimental conditions . Primary antibody incubation should be performed overnight at 4°C for optimal signal-to-noise ratio.

• Expected results: Anticipate detecting LRCH3 at approximately 70 kDa despite its calculated weight of 86 kDa . This discrepancy is not uncommon in protein research and may reflect post-translational modifications or protein folding characteristics.

• Positive controls: Human liver, heart, and spleen tissues, as well as Jurkat cells and mouse lung tissue, have been validated as positive controls for LRCH3 expression .

How should researchers approach immunofluorescence experiments for LRCH3 localization studies?

For successful immunofluorescence localization of LRCH3:

• Cell/tissue preparation: Fixation with 4% paraformaldehyde works well for most applications, though methanol fixation can be tested as an alternative if initial results are suboptimal.

• Permeabilization: Use 0.1-0.3% Triton X-100 for adequate permeabilization without disrupting cellular architecture.

• Blocking: To minimize non-specific binding, block with 1-5% BSA or normal serum in PBS for 30-60 minutes at room temperature.

• Primary antibody: Incubate with diluted LRCH3 antibody (1:200-1:800) in blocking solution overnight at 4°C or for 1-2 hours at room temperature.

• Controls: Include both technical controls (secondary antibody only) and biological controls (cell types known to express LRCH3, such as A431 cells) .

• Visualization: Counterstain with DAPI for nuclear visualization to provide cellular context for interpreting LRCH3 localization patterns.

• Analysis: When interpreting results, consider that subcellular localization may vary depending on cell type, cell cycle stage, and physiological conditions.

What considerations are important for immunoprecipitation experiments targeting LRCH3?

For successful immunoprecipitation (IP) of LRCH3:

• Antibody amount: Use 0.5-4.0 μg of LRCH3 antibody for 1.0-3.0 mg of total protein lysate . The precise amount may need optimization depending on expression levels in your experimental system.

• Lysis conditions: Use non-denaturing lysis buffers containing protease inhibitors to preserve protein-protein interactions while effectively solubilizing LRCH3.

• Pre-clearing: Pre-clear lysates with protein A/G beads to reduce non-specific binding, which can be particularly important when studying novel interaction partners.

• Incubation times: Allow sufficient time (typically overnight at 4°C) for antibody-antigen binding before adding capture beads.

• Washing stringency: The stringency of washing buffers should be optimized to maintain specific interactions while removing non-specific binding partners.

• Controls: Include isotype control antibodies and, when possible, LRCH3-depleted samples as negative controls.

• Detection methods: For downstream analysis, consider both traditional Western blotting and more sensitive techniques such as mass spectrometry for identifying novel interaction partners.

How can researchers address challenges in antibody specificity verification?

Ensuring LRCH3 antibody specificity is critical for reliable research outcomes:

• Multiple validation approaches:

  • Compare results across different detection methods (WB, IF, IP)

  • Use genetic knockdown/knockout systems as definitive negative controls

  • Perform peptide competition assays to confirm epitope-specific binding

  • Compare results with multiple antibodies targeting different LRCH3 epitopes

• Addressing potential cross-reactivity:

  • Cross-reference observed patterns with mRNA expression data

  • Consider mass spectrometry validation of immunoprecipitated material

  • Test reactivity in systems with variable LRCH3 expression levels

• Technical considerations:

  • Optimize blocking conditions to minimize non-specific binding

  • Titrate antibody concentrations to determine optimal signal-to-noise ratio

  • Include appropriate negative and positive controls in each experiment

What are common troubleshooting strategies for weak or inconsistent LRCH3 detection?

When facing challenges with LRCH3 detection:

• Sample preparation optimization:

  • Ensure complete lysis and solubilization using appropriate buffers

  • Include fresh protease inhibitors to prevent degradation

  • Consider tissue-specific extraction protocols for difficult samples

• Detection sensitivity enhancement:

  • Increase primary antibody concentration or incubation time

  • Use more sensitive detection systems (enhanced chemiluminescence, fluorescent secondary antibodies)

  • Consider signal amplification methods for low-abundance detection

• Technical adjustments:

  • For Western blotting: optimize transfer conditions, try different membrane types

  • For immunofluorescence: test alternative fixation and permeabilization methods

  • For immunoprecipitation: adjust antibody-to-lysate ratios and incubation conditions

• Experimental design considerations:

  • Include positive control samples known to express LRCH3 (human liver, heart, spleen tissue, Jurkat cells, or mouse lung tissue)

  • Run parallel experiments with different antibodies targeting LRCH3

  • Consider the impact of experimental conditions on LRCH3 expression or modification

How can researchers accurately interpret variable molecular weight observations for LRCH3?

The discrepancy between LRCH3's calculated (86 kDa) and observed (70 kDa) molecular weights requires careful interpretation:

• Potential explanations:

  • Post-translational modifications affecting protein mobility

  • Alternative splicing producing different isoforms

  • Proteolytic processing under certain conditions

  • Anomalous migration due to protein structure or charge distribution

• Verification approaches:

  • Compare migration patterns across different gel systems and buffer conditions

  • Use protein mass spectrometry to confirm actual protein mass

  • Investigate potential tissue-specific or condition-specific variations

  • Consider phosphatase or glycosidase treatments to assess contribution of modifications

• Experimental documentation:

  • Always report both expected and observed molecular weights

  • Include molecular weight markers in figure presentations

  • Discuss potential explanations for discrepancies in research reports

This careful attention to molecular weight variations can provide valuable insights into LRCH3 biology and prevent misinterpretation of experimental results.

How can LRCH3 antibodies be utilized in studies of protein-protein interactions?

Investigating LRCH3 protein interactions requires specialized approaches:

• Co-immunoprecipitation strategies:

  • Use optimized lysis conditions to preserve protein complexes

  • Consider chemical crosslinking for transient interactions

  • Employ reciprocal co-IP (immunoprecipitating with antibodies against suspected interaction partners)

  • Use mass spectrometry for unbiased identification of interaction partners

• Proximity-based approaches:

  • Proximity ligation assays (PLA) for in situ detection of protein interactions

  • BioID or APEX proximity labeling with LRCH3 fusion proteins

  • FRET-based approaches for studying dynamic interactions

• Structural considerations:

  • Evaluate antibody epitope location relative to potential interaction domains

  • Consider the impact of antibody binding on protein complex formation

  • Design experiments to detect both stable and transient interactions

• Functional validation:

  • Correlate interaction data with functional readouts

  • Use mutagenesis approaches to map interaction domains

  • Consider the effects of physiological stimuli on LRCH3 interactions

These approaches can provide valuable insights into LRCH3's biological function through identification of its interaction network.

What considerations are important when studying LRCH3 in disease models?

When investigating LRCH3 in disease contexts:

• Expression analysis:

  • Compare LRCH3 levels between healthy and diseased tissues

  • Assess potential alterations in subcellular localization

  • Investigate post-translational modifications under pathological conditions

• Genetic approaches:

  • Generate or utilize LRCH3 knockout/knockdown models

  • Study the phenotypic consequences of LRCH3 modulation

  • Consider rescue experiments to confirm specificity

• Methodological considerations:

  • Use multiple antibodies targeting different epitopes

  • Compare protein expression with mRNA levels

  • Consider tissue-specific effects and cell-type heterogeneity

• Translational aspects:

  • Correlate experimental findings with clinical data when available

  • Consider potential diagnostic or therapeutic implications

  • Evaluate LRCH3 in relevant model systems that recapitulate disease features

Such studies can contribute to understanding LRCH3's potential role in pathological processes and identify new therapeutic targets.

How can computational approaches enhance LRCH3 antibody-based research?

Modern computational tools can significantly elevate LRCH3 research:

• Antibody-epitope predictions:

  • Use epitope prediction algorithms to understand antibody binding sites

  • Model potential cross-reactivity with similar epitopes in other proteins

  • Predict accessibility of epitopes in the folded protein structure

• Structure-function analyses:

  • Predict LRCH3 tertiary structure using tools like AlphaFold2

  • Identify potential functional domains and interaction surfaces

  • Model the impact of post-translational modifications

• Image analysis enhancements:

  • Employ machine learning algorithms for automated quantification of immunostaining

  • Develop colocalization analyses with subcellular markers

  • Implement 3D reconstruction techniques for complex tissues

• Integrative approaches:

  • Combine LRCH3 protein data with transcriptomic and proteomic datasets

  • Network analysis to identify functional pathways involving LRCH3

  • Prediction of potential regulatory mechanisms

While computational approaches provide valuable insights, researchers should be aware of current limitations in antibody structure prediction discussed in the literature , such as challenges in modeling CDR loops, particularly CDR-H3, which shows high diversity in length, sequence, and structure.

How might advanced microscopy techniques enhance LRCH3 localization studies?

Super-resolution microscopy offers new possibilities for LRCH3 research:

• Technique selection based on research questions:

  • STORM/PALM for nanoscale distribution and clustering analysis

  • STED microscopy for high-resolution intracellular localization

  • SIM for improved resolution while maintaining live-cell compatibility

• Antibody considerations for super-resolution:

  • Select fluorophores compatible with specific super-resolution techniques

  • Consider using smaller antibody formats (Fab fragments, nanobodies) for improved resolution

  • Validate specificity rigorously as signal amplification may exacerbate non-specific binding

• Sample preparation optimizations:

  • Adjust fixation protocols to preserve nanoscale structures

  • Optimize immunostaining conditions for high signal-to-background ratio

  • Consider tissue clearing techniques for thick tissue specimens

• Analysis approaches:

  • Quantitative assessment of LRCH3 clustering or nanodomain organization

  • Precise colocalization measurements with interaction partners

  • Correlation with functional readouts at subcellular resolution

These advanced imaging approaches can reveal previously undetectable aspects of LRCH3 distribution and function.

What are the prospects for using intracellular antibodies against LRCH3?

Intracellular antibody technologies offer promising approaches for LRCH3 functional studies:

• Format considerations:

  • Single-chain variable fragments (scFvs) for intracellular expression

  • Camelid nanobodies for enhanced stability in intracellular environments

  • Intrabodies targeted to specific subcellular compartments

• Delivery approaches:

  • Viral vector-mediated expression of intracellular antibodies

  • Cell-penetrating peptide conjugation for direct protein delivery

  • Lipid-based transfection of antibody-encoding mRNA

• Functional applications:

  • Protein knockout strategies using intracellular antibodies with degradation signals

  • Modulation of specific protein interactions

  • Real-time tracking of endogenous LRCH3 in living cells

• Therapeutic potential:

  • Investigation of LRCH3 as a potential therapeutic target

  • Development of intracellular antibody approaches for targeting disease-relevant pathways

As highlighted in recent research, intracellular antibody technologies are advancing for therapy aimed at hard-to-drug proteins , which could potentially include LRCH3 if it emerges as a disease-relevant target.

How might computational antibody design impact future LRCH3 research?

Emerging computational approaches are transforming antibody research:

• Structure-based antibody design:

  • Prediction of optimal antibody-antigen interactions

  • Design of antibodies with enhanced specificity for LRCH3 epitopes

  • Development of antibodies targeting specific functional domains

• Deep learning applications:

  • Diffusion probabilistic models for antibody design targeting specific antigens

  • Generation of antibodies with optimal binding and biophysical properties

  • Prediction of antibody-antigen binding affinities

• Practical research implications:

  • Development of more specific LRCH3 antibodies targeting distinct epitopes

  • Creation of antibody panels for comprehensive LRCH3 characterization

  • Tailored antibodies for specific applications (super-resolution imaging, intracellular targeting)

• Limitations and considerations:

  • Challenges remain in accurate prediction of antibody structures

  • Computational methods must be complemented by experimental validation

  • Rigorous quality control is needed to identify modeling artifacts

As computational methods continue to advance, they promise to accelerate the development of next-generation antibody tools for LRCH3 research.