LCR57 Antibody

What is LRRC57 and what cellular functions is it associated with?

LRRC57 (Leucine rich repeat containing 57) is a 239 amino acid protein that contains eight leucine-rich repeat (LRR) domains. The protein is encoded by a gene located on human chromosome 15q15.2. According to current research, LRRC57 is found in the extracellular region and can be secreted in extracellular exosomes. The protein is also found in membrane-associated locations, suggesting it may play a role in cellular signaling or structural organization .

What validated samples and applications exist for LRRC57 antibodies?

Current research has validated LRRC57 antibodies for immunohistochemistry (IHC) applications in specific human tissues. Validated samples include human colon cancer and human tonsil tissues . The recommended dilution for IHC applications is 1:50-1:200 . While the available search results indicate IHC as the primary validated application, researchers should consider testing the antibody in other applications such as Western blotting, immunoprecipitation, or flow cytometry based on experimental needs and with appropriate controls.

What is the typical structure and composition of commercially available LRRC57 antibodies?

The LRRC57 polyclonal antibody referenced in the search results is a rabbit IgG isotype antibody that recognizes the recombinant protein of human LRRC57 . This antibody is supplied at a concentration of 0.2 mg/mL in a phosphate-buffered solution (pH 7.4) containing 0.05% stabilizer and 50% glycerol . The antibody is purified using affinity purification methods to ensure specificity . Like other antibodies, it would consist of two heavy chains and two light chains connected by disulfide bonds, with the antigen-binding sites formed by the variable regions.

What are the optimal storage conditions for maintaining LRRC57 antibody activity?

For optimal preservation of antibody activity, LRRC57 antibodies should be stored at -20°C, where they remain stable for up to 12 months . It is crucial to avoid repeated freeze-thaw cycles as these can lead to protein denaturation and loss of binding activity. When shipping is necessary, the antibody should be transported with ice packs, and upon receipt, it should be immediately stored at the recommended temperature .

For long-term research projects, consider aliquoting the antibody into smaller volumes before freezing to minimize the number of freeze-thaw cycles. Each aliquot should be sufficient for a single experiment to preserve the antibody's integrity and ensure consistent results across experiments.

How should researchers validate LRRC57 antibodies for new applications or tissue samples?

When validating LRRC57 antibodies for new applications or tissue samples, researchers should follow a systematic approach:

• Positive and negative controls: Include known positive samples (e.g., human colon cancer or tonsil tissues that have been validated) and appropriate negative controls (tissues not expressing the target or samples from knockout models if available).

• Antibody titration: Perform a dilution series beyond the recommended 1:50-1:200 range to determine optimal concentration for your specific application.

• Multi-method validation: Compare results across different techniques (e.g., IHC, Western blot, immunofluorescence) to confirm specificity.

• Cross-reactivity assessment: Test the antibody against related proteins to ensure specificity, particularly important since LRRC57 contains leucine-rich repeats which are common structural motifs.

• Blocking experiments: Use recombinant LRRC57 protein (the immunogen used to produce the antibody) to block antibody binding and confirm specificity.

This systematic validation approach aligns with current best practices in antibody research and helps establish reliable experimental protocols.

How can researchers optimize immunohistochemistry protocols for LRRC57 detection?

To optimize immunohistochemistry protocols for LRRC57 detection, consider the following methodological improvements:

• Antigen retrieval optimization: Test multiple antigen retrieval methods (heat-induced epitope retrieval with citrate buffer pH 6.0 or EDTA buffer pH 9.0) to determine which best exposes the LRRC57 epitopes in your fixed tissue.

• Blocking optimization: Since LRRC57 has been identified in extracellular regions , use appropriate blocking sera (5-10% normal serum from the species of the secondary antibody) to reduce background staining.

• Primary antibody incubation: Start with the recommended dilution range (1:50-1:200) , but test multiple dilutions and incubation conditions (4°C overnight vs. room temperature for 1-2 hours).

• Detection system selection: For low-abundance proteins like LRRC57, consider amplification methods such as tyramide signal amplification or polymer-based detection systems.

• Counterstaining optimization: Adjust counterstaining intensity to provide cellular context without obscuring specific LRRC57 staining.

• Multiplexing considerations: If co-staining with other markers, ensure antibody compatibility (species, isotypes) and optimize the staining sequence.

Record all optimization steps systematically to establish a reproducible protocol for your specific research needs.

How might researchers apply CDR walking strategies to improve LRRC57 antibody affinity?

CDR (Complementarity Determining Region) walking is an advanced technique to optimize antibody binding sites through sequential mutation of CDRs. This approach could be valuable for enhancing LRRC57 antibody affinity through the following methodological steps:

• Initial affinity determination: Establish the baseline affinity of existing LRRC57 antibodies using surface plasmon resonance or bio-layer interferometry.

• CDR identification and mutation library creation: Design mutation libraries focusing on the CDRs, particularly CDR-H3, which often contributes significantly to antigen specificity.

• Sequential optimization: Apply stepwise mutagenesis, where after each round of mutation, the highest-affinity variant becomes the template for subsequent rounds .

• Selection process: Use phage, yeast, or mammalian display technologies to select for improved variants.

• Validation of improved antibodies: Confirm enhanced binding using multiple methods and ensure specificity is maintained.

This approach has demonstrated significant improvements in antibody affinity in other systems. For example, Yang et al. developed an anti-HIV gp120 Fab with a 420-fold increase in affinity (Kd=1.5×10^-11 M) using CDR walking strategies, while Schier et al. produced an anti-c-erbB-2 scFv with picomolar affinity (Kd=1.3×10^-11 M) . Similar improvements might be achievable for LRRC57 antibodies.

What computational approaches could accelerate LRRC57 antibody engineering?

Several computational tools can be employed to accelerate LRRC57 antibody engineering:

• Ab initio design tools: Programs like OptCDR, OptMAVEn, AbDesign, and RosettaAntibodyDesign can enable rational design of antibodies based on structural predictions of the antibody-antigen interface .

• Interface prediction tools: Software such as Antibody i-Patch, Paratome, proABC, Parapred, and Antibody Interface Prediction can help identify potential paratopes in the antibody structure that would optimally interact with LRRC57 .

• Epitope prediction tools: ASEP, BEPAR, ABEpar, EpiPred, PEASE, and MabTope can predict potential epitopes on LRRC57, guiding antibody design to target the most accessible and specific regions .

• Molecular docking software: ClusPro, SurFit, FRODOCK, and SnugDock can model the interaction between designed antibodies and LRRC57, allowing for in silico screening before experimental validation .

• Machine learning approaches: Deep learning models trained on antibody-antigen interaction data can predict affinity and specificity, potentially identifying optimal antibody candidates.

The integration of these computational approaches with experimental validation can significantly reduce the time and resources required for developing high-affinity LRRC57 antibodies.

How can structural biology inform better LRRC57 antibody design?

Structural biology offers powerful insights for LRRC57 antibody design through several methodological approaches:

• Co-crystallization studies: Determining the crystal structure of the LRRC57-antibody complex at high resolution (ideally 2.0-3.0 Å, similar to the resolution range of 2.15-3.0 Å achieved in HIV-1 antibody studies) would provide atomic-level details of the interaction interface.

• Epitope mapping: By analyzing the antibody-LRRC57 complex structure, researchers can identify critical contact residues that contribute significantly to binding affinity and specificity.

• Structural comparison: Analyzing multiple antibody-LRRC57 complexes can reveal conserved binding modes and variable regions that could be targeted for optimization, similar to the approach used in HIV-1 antibody analysis .

• Structure-guided mutagenesis: Based on structural data, researchers can design rational mutations to enhance complementarity between the antibody CDRs and LRRC57 epitopes.

• Framework optimization: Structural analysis can guide modifications to the antibody framework regions to improve stability without compromising antigen binding.

This approach has proven successful in other systems, such as the detailed structural analysis of VRC01-class antibodies against HIV-1, where crystal structures of antibody-gp120 complexes from multiple donors provided crucial insights into antibody evolution and design .

What are common causes of non-specific binding with LRRC57 antibodies and how can they be mitigated?

Non-specific binding is a common challenge in antibody-based experiments. For LRRC57 antibodies, consider these causes and solutions:

• Insufficient blocking: Since LRRC57 is found in extracellular regions and membranes , use appropriate blocking agents that match your sample type (e.g., 5% BSA, 5-10% normal serum, or commercial blocking buffers).

• Cross-reactivity with related proteins: LRRC57 contains leucine-rich repeats, which are common structural motifs. To reduce cross-reactivity:

  • Increase antibody dilution beyond the standard 1:50-1:200 range

  • Pre-absorb the antibody with related proteins

  • Use highly purified recombinant LRRC57 as a competitive inhibitor

• Fc receptor binding: If working with tissues rich in Fc receptor-expressing cells (e.g., immune cells), include an Fc blocking step before applying the primary antibody.

• Fixation artifacts: Optimize fixation protocols to preserve the native epitope structure while maintaining tissue morphology.

• Endogenous enzyme activity: When using HRP or AP-based detection systems, include appropriate endogenous enzyme inhibition steps.

• Autofluorescence: If using fluorescent detection, employ autofluorescence quenching reagents and select fluorophores that avoid spectral overlap with autofluorescent components.

Systematic testing of these interventions will help establish a protocol with optimal signal-to-noise ratio for your specific experimental system.

How can researchers distinguish between true LRRC57 signal and background in low-expression samples?

Distinguishing true LRRC57 signal from background in low-expression samples requires a combination of technical and analytical approaches:

• Multiple antibody validation: Use two or more antibodies targeting different epitopes of LRRC57 to confirm staining patterns.

• Signal amplification methods: Consider tyramide signal amplification or polymer-based detection systems to enhance sensitivity without increasing background.

• Quantitative image analysis: Employ digital image analysis with appropriate thresholding to objectively distinguish signal from background.

• Comparison with mRNA expression: Correlate protein detection with mRNA expression using techniques like in situ hybridization or RT-PCR from adjacent sections.

• Genetic controls: Where possible, use samples with genetically manipulated LRRC57 expression (overexpression or knockdown) as reference points.

• Z-stack imaging: In fluorescence microscopy, use optical sectioning and z-stack acquisition to differentiate true signal from autofluorescence or artifacts.

• Complementary approaches: Validate findings using orthogonal techniques such as Western blotting or mass spectrometry-based proteomics.

This multi-faceted approach helps ensure that detected signals truly represent LRRC57 rather than technical artifacts, particularly important when studying tissues with naturally low expression levels.

What are emerging applications for studying LRRC57 in disease contexts?

While specific research on LRRC57 in disease contexts is still developing, its location on chromosome 15q15.2 suggests potential relevance to several disease areas . Emerging applications include:

• Cancer research: Given the validation of LRRC57 antibodies in colon cancer tissues , investigating its expression patterns across cancer types could reveal diagnostic or prognostic biomarker potential.

• Neurological disorders: Since chromosome 15 houses genes implicated in neurological conditions like Angelman syndrome and Prader-Willi syndrome , exploring LRRC57's role in neural development or function may be valuable.

• Immune regulation: The presence of LRRC57 in tonsil tissue and its extracellular localization suggest potential involvement in immune processes, warranting investigation in inflammatory or autoimmune conditions.

• Developmental biology: LRR-containing proteins often function in developmental pathways, making LRRC57 a candidate for studies in embryonic development and differentiation.

• Protein-protein interaction networks: Identifying binding partners of LRRC57 could place it within cellular signaling pathways relevant to disease.

Each of these applications would benefit from the development of well-characterized LRRC57 antibodies and may provide insights into previously unrecognized disease mechanisms.

How might single-cell approaches advance understanding of LRRC57 expression patterns?

Single-cell approaches offer powerful new ways to understand LRRC57 expression patterns:

• Single-cell RNA sequencing (scRNA-seq): This can reveal cell type-specific expression patterns of LRRC57 across tissues and disease states, providing context for antibody-based protein detection.

• Mass cytometry (CyTOF): By incorporating LRRC57 antibodies into CyTOF panels, researchers can analyze its expression in relation to dozens of other markers simultaneously, revealing associations with specific cellular phenotypes.

• Spatial transcriptomics: Techniques like Visium or MERFISH can map LRRC57 expression within tissue architecture, providing spatial context that traditional methods lack.

• Single-cell proteomics: Emerging methods for single-cell protein analysis could reveal post-transcriptional regulation of LRRC57 expression not captured by RNA-based methods.

• Live-cell imaging: Using fluorescently tagged antibody fragments to track LRRC57 in living cells can reveal dynamic aspects of its localization and trafficking.

These single-cell approaches could be particularly valuable given LRRC57's presence in both membrane and extracellular compartments , potentially revealing heterogeneous expression or secretion patterns that would be masked in bulk analyses.

What novel antibody technologies might enhance LRRC57 research?

Several cutting-edge antibody technologies could substantially advance LRRC57 research:

• Nanobodies/single-domain antibodies: Derived from camelid antibodies (similar to those developed from llamas for other applications) , these smaller antibody fragments could provide better tissue penetration and access to sterically hindered epitopes of LRRC57.

• Bispecific antibodies: Antibodies engineered to simultaneously bind LRRC57 and another protein of interest could help investigate protein-protein interactions or co-localization.

• Intrabodies: Antibodies specifically engineered to function within cells could help study intracellular pools of LRRC57 in living systems.

• Antibody-drug conjugates: For therapeutic applications, LRRC57 antibodies could be conjugated to drugs for targeted delivery to cells expressing this protein.

• Conditionally activated antibodies: Antibodies designed to bind LRRC57 only under specific conditions (pH, protease activity, etc.) could provide insights into microenvironmental regulation.

• Proximity labeling antibodies: Antibodies conjugated with enzymes that catalyze biotinylation of nearby proteins could help identify the LRRC57 interactome.

These technologies extend beyond traditional antibody applications and could reveal new biological functions and therapeutic opportunities for targeting LRRC57.

What are the key specifications for LRRC57 antibodies currently available for research?

What are reported synonyms and identifiers for LRRC57?