ARR15 Antibody

What are LRRC15 and ACTR5 proteins, and why are they important research targets?

LRRC15 (Leucine-rich repeat-containing protein 15) is a protein implicated in various cellular processes, particularly in infection pathways. LRRC15 has gained significant research interest due to its role in modulating SARS-CoV-2 infection of host cells through interaction with the spike protein. It does not act as a direct entry receptor but rather sequesters virions and antagonizes SARS-CoV-2 infection of ACE2-positive cells when expressed on nearby cells . This makes it a valuable target for infectious disease research.

ACTR5 (also known as Arp5) belongs to the family of nuclear actin-related proteins (ARPs) that function as components of chromatin-remodeling complexes. Recent studies have shown that Arp5 regulates smooth muscle cell differentiation through interaction with myocardin (Myocd) . This connection to cellular differentiation pathways makes ACTR5 an important research target for developmental biology and cellular differentiation studies.

What are the validated applications for LRRC15 and ACTR5 antibodies?

LRRC15 antibodies such as EPR8188(2) have been validated for multiple research applications including immunofluorescence (ICC/IF) and western blot (WB) in human, mouse, and rat samples . They are particularly useful for studying LRRC15's role in viral infection pathways.

For ACTR5/Arp5 antibodies like 21505-1-AP, the validated applications include:

• Western Blot (WB): Recommended dilution of 1:1000-1:6000

• Immunoprecipitation (IP): 0.5-4.0 μg for 1.0-3.0 mg of total protein lysate

• Immunofluorescence (IF)/ICC: 1:10-1:100

The applications have been validated across multiple tissue and cell types, including HEK-293 cells, human skeletal muscle tissue, mouse cerebellum tissue, mouse heart tissue, mouse ovary tissue, and rat heart tissue for WB applications .

How should researchers validate antibody specificity before experimental use?

Validating antibody specificity requires a multi-faceted approach:

• Western blot analysis with appropriate positive and negative controls to confirm the antibody detects a protein of the expected molecular weight. For example, LRRC15 antibody detection shows bands at approximately 70-80 kDa in human skin and U-118-MG human glioblastoma/astrocytoma cell lines .

• Test across multiple cell lines or tissues known to express the target protein. For example, ACTR5 antibody has been validated in HEK-293 cells, human skeletal muscle tissue, and various mouse and rat tissues .

• Include knockdown/knockout validation where possible. The ACTR5 antibody has been cited in at least two studies using KD/KO approaches, confirming specificity .

• Multi-assay validation is critical - an antibody should be tested across different applications (WB, IP, IF) when possible to confirm consistent target recognition across platforms.

• Consider employing tissue microarray (TMA) validation for immunohistochemistry applications, as was done for androgen receptor antibodies .

How can LRRC15 antibodies be utilized in SARS-CoV-2 research?

LRRC15 antibodies have become valuable tools in SARS-CoV-2 research due to the protein's interaction with the viral spike protein. Using these antibodies, researchers can:

• Track LRRC15 expression patterns in various cell types to identify potential sites of viral sequestration.

• Perform co-immunoprecipitation experiments to isolate and study LRRC15-spike protein complexes, helping to elucidate the molecular mechanisms of interaction.

• Utilize immunofluorescence microscopy to visualize the cellular localization of LRRC15 during viral infection, particularly its role in sequestering virions away from ACE2-positive cells.

• Develop cell-based assays to quantify LRRC15's antagonistic effect on SARS-CoV-2 infection, potentially as a screening platform for therapeutics that might enhance this protective function .

When designing these experiments, researchers should carefully select antibodies validated for the specific application and include appropriate controls to distinguish LRRC15-specific effects from background interactions.

What methodological approaches enable single-cell analysis of protein expression using these antibodies?

Single-cell analysis of protein expression using antibodies like those against AR has been effectively implemented through high-throughput microscopy. The methodology includes:

• Cell preparation: Treating cells with compounds of interest (such as DHT or endocrine disrupting chemicals) across concentration gradients.

• Immunostaining: Using validated antibodies at optimized concentrations to detect the target protein.

• High-throughput imaging: Acquiring images from multiple fields to capture thousands of individual cells.

• Data normalization: Median and MAD (median absolute deviation) normalization based on positive control treatments, especially important for non-normal distributions.

• Distribution analysis: Creating histograms with appropriate binning (e.g., 25 bins based on the square root of the smallest number of experimental observations).

• Statistical evaluation: Applying two-sample Kolmogorov-Smirnov tests to measure distances between experimental distributions across replicates.

• Heterogeneity quantification: Calculating indices such as the Shannon Index to measure population heterogeneity .

This approach allows researchers to capture the full distribution of protein expression across cell populations, revealing subpopulations and response heterogeneity that might be missed in bulk analyses.

How do antibody engineering techniques impact research antibody performance?

Antibody engineering significantly affects research antibody performance through several mechanisms:

• Class switching can alter in vivo effector function and stability. For example, reformatting from IgG to IgM can be valuable for infectious disease research and diagnostic assay development, as demonstrated during COVID-19 research with anti-coronavirus spike glycoprotein antibodies .

• Molecular size engineering affects tissue penetration and half-life. Antibodies smaller than the renal filtration limit (30-50 kDa) clear within hours, while those above this limit but without FcRn binding capability have moderate half-lives (days in humans). Antibodies that can bind FcRn have extended half-lives (weeks in humans) .

• Fc fusion engineering creates molecules with specialized properties. Classical homodimeric Fc fusions combine the targeting specificity of the binding domain with the effector functions and extended half-life of the Fc region .

• Sequence optimization improves physicochemical properties to reduce aggregation tendencies and enhance thermal and colloidal stability, factors critical for reproducible experimental results .

For research antibodies, these engineering approaches allow for customization to specific experimental needs, whether that involves extended tissue retention, rapid clearance, or specialized detection capabilities.

What dilution optimization strategies should researchers employ for different applications?

Optimizing antibody dilutions is critical for obtaining specific signals while minimizing background. Application-specific strategies include:

For Western Blot:

• Start with the manufacturer's recommended range (e.g., 1:1000-1:6000 for ACTR5 antibody)

• Perform a dilution series across this range on samples with known expression levels

• Consider sample type variations; different tissues may require adjusted dilutions

• Evaluate signal-to-noise ratio at each dilution point

• For weak signals, longer exposure times are preferable to excessive antibody concentration

For Immunofluorescence/ICC:

• Begin with lower dilutions (e.g., 1:10-1:100 for ACTR5)

• Include a negative control at each dilution to assess background

• Optimize blocking conditions alongside antibody dilution

• Consider extended incubation at lower concentrations versus shorter times at higher concentrations

For Immunoprecipitation:

• Calculate based on total protein amount (e.g., 0.5-4.0 μg antibody for 1.0-3.0 mg protein)

• Perform pilot experiments with varying antibody-to-bead ratios

• Pre-clear lysates thoroughly to reduce non-specific binding

The final optimized dilution should be determined empirically for each experimental system, as factors such as target abundance, sample preparation method, and detection system sensitivity all influence the optimal working concentration.

What are the proper storage and handling procedures to maintain antibody activity?

To maintain antibody activity and ensure reproducible results, researchers should follow these storage and handling guidelines:

Proper storage and handling significantly impact experimental reproducibility and should be considered essential aspects of experimental design.

How should researchers approach data analysis for antibody-based assays?

Data analysis for antibody-based assays requires rigorous statistical approaches tailored to the specific assay format and research question:

• For Western blot quantification:

  • Use appropriate normalization controls (housekeeping proteins)

  • Apply densitometric analysis with software that can account for background and saturation

  • Consider biological replicates (n≥3) for statistical testing

  • Use non-parametric tests if normality cannot be assumed

• For high-throughput microscopy and single-cell analysis:

  • Apply median and MAD (median absolute deviation) normalization when distributions are non-normal

  • Create histograms with appropriate binning (e.g., 25 bins based on the square root of the smallest number of observations)

  • Use Kolmogorov-Smirnov tests to measure distances between experimental distributions

  • Consider Shannon Index calculations to quantify population heterogeneity

• For multi-assay integration:

  • Calculate pairwise Spearman's correlation coefficients between assays

  • Consider approaches like ToxPi for integrating multiple endpoints

  • Note that correlation between assays may vary by mode (e.g., agonist versus antagonist modes)

• Visualization approaches:

  • Generate heatmaps to visualize relationships across multiple parameters

  • Use curve fitting in GraphPad Prism or similar software for dose-response relationships

  • Apply normalization appropriate to the experimental design (e.g., range normalization for ToxPi analysis)

The choice of statistical method should be justified based on data distribution and experimental design, with appropriate attention to sample size, replicate structure, and potential confounding variables.

What controls are essential when using these antibodies in different experimental setups?

Implementing appropriate controls is critical for ensuring the validity of antibody-based experiments:

• For Western Blot:

  • Positive control: Lysates from cells/tissues known to express the target (e.g., HEK-293 cells, human skeletal muscle tissue for ACTR5)

  • Negative control: Lysates from cells with target knockout or from tissues known not to express the target

  • Loading control: Housekeeping protein detection to normalize for total protein loading

  • Secondary antibody-only control: To detect non-specific binding of the secondary antibody

• For Immunofluorescence/ICC:

  • Positive control: Cells known to express the target (e.g., A549 cells, HepG2 cells for ACTR5)

  • Negative control: Cells with target knockout or primary antibody omission

  • Counterstaining: Nuclear stain (DAPI) for cell identification and localization context

  • Autofluorescence control: Unstained sample to establish background fluorescence levels

• For Immunoprecipitation:

  • Input control: Small aliquot of pre-IP lysate to verify target presence

  • IgG control: Non-specific IgG of same species and isotype as primary antibody

  • Beads-only control: To identify non-specific binding to beads

  • Reciprocal IP: When studying protein interactions, confirm with IP of interaction partner

• For high-throughput assays:

  • Positive control treatments: e.g., DHT 100nM for androgen receptor studies

  • Vehicle control: To establish baseline response

  • Technical replicates: Minimum of four per treatment condition

  • Biological replicates: Minimum of two independent experiments

These controls should be tailored to the specific experimental question and incorporated into both the experimental design and data analysis pipeline.

How can researchers integrate antibody-based assays with other research technologies?

Integration of antibody-based assays with complementary technologies enhances research depth and addresses limitations of individual approaches:

• Integration with orthogonal assays:

  • Combine antibody-based protein detection with transcriptomic approaches to correlate protein levels with gene expression

  • Integrate with functional assays to connect protein detection to biological activity

  • Use the ToxPi approach to integrate multiple endpoints from different assay types, as demonstrated with androgen receptor studies

• Correlation analysis across platforms:

  • Calculate Spearman's correlation coefficients between assays to identify concordance and discordance

  • Note that correlation strength may vary by experimental mode (e.g., agonist versus antagonist modes showed different correlation patterns in AR studies)

  • Identify complementary assays with low correlation to maximize information gain

• Multi-parameter analysis:

  • Combine antibody staining with other fluorescent reporters for multiparameter single-cell analysis

  • Integrate image-based features with biochemical measurements

  • Apply machine learning approaches to identify patterns across diverse data types

• Technology-specific considerations:

  • When combining with mass spectrometry, use antibodies for target enrichment before analysis

  • For integration with genomic data, consider epitope availability in different genetic variants

  • When complementing functional assays, ensure compatible experimental conditions

This integrated approach provides a more comprehensive understanding of biological systems and increases confidence in experimental findings through convergent evidence.

What advances in antibody developability assessment impact research applications?

Recent advances in antibody developability assessment have significant implications for research applications:

• High-throughput developability workflows:

  • Implementation of efficient screening pipelines evaluating hundreds to thousands of antibody molecules

  • Integration of developability assessment during early antibody generation and screening

  • Evaluation of critical developability parameters alongside binding affinity and biological properties using small amounts of purified material

• Key developability parameters assessed:

  • Self-interaction and aggregation tendency

  • Thermal stability

  • Colloidal stability

  • Optimization potential through sequence engineering

• Impact on research applications:

  • More robust antibodies with consistent performance across experiments

  • Reduced batch-to-batch variability through recombinant formats

  • Extended shelf-life and stability during experimental procedures

  • Improved reproducibility of research findings

• Implementation considerations:

  • Antibody format selection should consider the specific research application

  • Molecular size affects both tissue penetration and half-life, requiring thoughtful balance

  • Class switching can overcome aggregation issues with certain subtypes

  • Fc engineering enables customization of effector functions for specialized research applications

By selecting antibodies with favorable developability profiles, researchers can enhance experimental consistency and reduce technical variability in their studies.

What future directions are emerging for antibody-based research on LRRC15 and ACTR5?

Future research directions for LRRC15 and ACTR5 antibodies are shaped by both technological advances and emerging biological insights:

• For LRRC15 research:

  • Expanded investigation of its role in SARS-CoV-2 pathogenesis and potential therapeutic targeting

  • Development of more specific antibodies targeting functional domains involved in viral interactions

  • Application in diagnostic platforms for infectious disease monitoring

  • Exploration of roles beyond viral infection in tissue development and disease processes

• For ACTR5/Arp5 research:

  • Further characterization of its role in chromatin remodeling and transcriptional regulation

  • Investigation of its interaction with myocardin and implications for smooth muscle cell differentiation

  • Development of conditional knockout models to study tissue-specific functions

  • Exploration of potential roles in disease contexts

• Technological advancements:

  • Implementation of spatial proteomics approaches using antibodies against LRRC15 and ACTR5

  • Development of proximity labeling techniques to identify novel interaction partners

  • Application of advanced imaging methodologies to track dynamic changes in protein localization

  • Integration with CRISPR-based functional genomics screens

• Translational applications:

  • Exploration of LRRC15's potential as a therapeutic target for viral infections

  • Investigation of ACTR5's role in developmental disorders and potential diagnostic applications

  • Development of screening platforms to identify modulators of these proteins' activities

These emerging directions will continue to expand our understanding of these important proteins and their roles in fundamental biological processes and disease.

What methodological challenges remain in antibody-based protein analysis?

Despite significant advances, several methodological challenges persist in antibody-based protein analysis:

• Reproducibility challenges:

  • Batch-to-batch variation in antibody performance

  • Standardization of antibody validation across laboratories

  • Consistent reporting of antibody validation methods in publications

  • Variable antibody performance across different experimental conditions

• Technical limitations:

  • Detection of low-abundance proteins in complex samples

  • Quantification accuracy across wide dynamic ranges

  • Cross-reactivity with closely related proteins

  • Accessibility of epitopes in native protein conformations and complexes

• Data analysis considerations:

  • Integration of single-cell heterogeneity data with bulk measurements

  • Standardization of analysis methods for high-content imaging data

  • Development of robust statistical approaches for non-normal distributions common in protein expression data

  • Correlation of antibody-based measurements with orthogonal approaches

• Application-specific challenges:

  • Optimization for emerging technologies like spatial proteomics

  • Development of antibodies that function in diverse experimental conditions

  • Detection of post-translational modifications with high specificity

  • Assessment of protein-protein interactions in native contexts