CASTOR3 Antibody

What is CASTOR3 and its relationship to the CASTOR protein family?

CASTOR3 (Cellular Arginine Sensor for mTORC1 protein 3) belongs to the CASTOR family of proteins that function as arginine sensors in the mTORC1 pathway. While CASTOR1 and CASTOR2 have been well-characterized as arginine sensors that interact with the GATOR2 complex, CASTOR3 is a related protein with a putative similar structural architecture . CASTOR1 has been established as an arginine-binding protein that dissociates from GATOR2 upon arginine binding, thereby regulating mTORC1 signaling. In contrast, CASTOR2 doesn't directly bind arginine but can heterodimerize with CASTOR1 . CASTOR3 likely shares functional similarities with these proteins, though specific research on its exact role is still emerging.

What are the key applications of CASTOR3 Antibody in cellular research?

CASTOR3 Antibody is primarily used to detect and analyze CASTOR3 protein in various cell types and tissue samples. Key applications include:

• Western blot analysis for protein expression quantification

• Immunohistochemistry (IHC) for localization studies in tissue sections

• ELISA for quantitative measurement in samples

• Investigating CASTOR3's role in cellular signaling pathways, particularly in relation to mTORC1 regulation

These applications enable researchers to study CASTOR3's distribution, expression levels, and potential functional roles in normal and pathological conditions.

What technical specifications should researchers know about CASTOR3 Antibody?

The CASTOR3 Antibody (such as PACO61073) has specific technical characteristics that researchers should consider when designing experiments:

This antibody has been validated for detecting human CASTOR3 protein in immunohistochemistry applications, as demonstrated in human liver cancer tissue samples .

How does CASTOR3 compare functionally with CASTOR1 and CASTOR2 in mTORC1 signaling?

Based on structure-function relationships observed in the CASTOR family, CASTOR3 likely shares some functional characteristics with CASTOR1 and CASTOR2, though with distinct regulatory properties. CASTOR1 functions as a direct arginine sensor that binds arginine with a dissociation constant of approximately 30 μM, causing it to dissociate from GATOR2 and enabling mTORC1 activation . CASTOR2 cannot bind arginine but heterodimerizes with CASTOR1, affecting its function .

When investigating CASTOR3, researchers should consider:

• Whether CASTOR3 binds arginine or other amino acids

• Potential homo- and heterodimerization patterns (similar to CASTOR1-CASTOR2)

• Interaction with GATOR2 components

• Impact on downstream mTORC1 signaling

Experimental approaches comparing arginine-binding capacity, protein-protein interactions, and effects on mTORC1 pathway activation when CASTOR3 is depleted or overexpressed would help elucidate its specific functions.

What are the optimal experimental conditions for using CASTOR3 Antibody in co-immunoprecipitation studies?

When designing co-immunoprecipitation experiments to study CASTOR3 protein interactions:

• Cell Preparation: Transfect cells (e.g., HEK-293T) with expression plasmids for CASTOR3 and potential interacting partners, such as GATOR2 components

• Lysis Conditions: Use a buffer containing 40 mM HEPES pH 7.4, 2 mM MgCl₂, 10 mM KCl, and 0.3% CHAPS (or similar gentle detergent)

• Immunoprecipitation Protocol:

  • Incubate cell lysates with anti-CASTOR3 antibody at a 1:100 dilution

  • Add protein G agarose beads and incubate at 4°C with gentle rotation

  • Wash beads 3-5 times with lysis buffer

  • Elute bound proteins and analyze by immunoblotting

• Controls:

  • Include IgG control immunoprecipitation

  • Perform reverse immunoprecipitation with antibodies against suspected binding partners

  • Include amino acid stimulation/starvation conditions to assess regulatory effects

This approach is based on successful protocols used for studying CASTOR1 and CASTOR2 interactions , adapted for CASTOR3 research.

How can researchers differentiate between CASTOR3 and other CASTOR proteins in experimental settings?

Differentiating between CASTOR family members requires careful experimental design:

• Antibody Selection: Use antibodies targeting unique epitopes in CASTOR3 not present in CASTOR1/2

• Expression Analysis:

  • Use RT-qPCR with primer pairs specific to non-homologous regions

  • Perform western blotting with careful attention to molecular weight differences

  • Consider epitope-tagged constructs for overexpression studies

• Functional Assays:

  • Assess arginine binding capacity similar to methods used for CASTOR1/2

  • Evaluate interaction with GATOR2 components through co-immunoprecipitation

  • Analyze effects on mTORC1 signaling (S6K and 4E-BP1 phosphorylation)

• Knockout/Knockdown Validation:

  • Generate specific siRNA or CRISPR-based approaches targeting unique regions

  • Confirm specificity by rescuing with corresponding cDNA constructs

Careful experimental design and appropriate controls are essential for distinguishing the specific roles of CASTOR3 from other family members.

What are the critical parameters for optimizing CASTOR3 Antibody use in immunohistochemistry?

Optimizing CASTOR3 Antibody for immunohistochemistry requires attention to several parameters:

• Tissue Preparation:

  • Fixation: 10% neutral buffered formalin for 24 hours

  • Embedding: Paraffin embedding following standard protocols

  • Sectioning: 4-5 μm thick sections on charged slides

• Antigen Retrieval:

  • Method: Heat-induced epitope retrieval

  • Buffer: 10 mM citrate buffer (pH 6.0) or EDTA buffer (pH 9.0)

  • Conditions: 95-100°C for 20 minutes

• Antibody Protocol:

  • Blocking: 5% normal goat serum, 30-60 minutes

  • Primary antibody: 1:200-1:500 dilution of CASTOR3 Antibody (PACO61073)

  • Incubation: Overnight at 4°C or 1-2 hours at room temperature

  • Detection system: HRP-polymer and DAB chromogen

• Validation Controls:

  • Positive control: Human liver cancer tissue (known to express CASTOR3)

  • Negative controls: Primary antibody omission and isotype control

  • Absorption control: Pre-incubate antibody with immunizing peptide

The optimal dilution should be determined empirically for each application and tissue type, starting with the manufacturer's recommended range of 1:200-1:500 .

How should researchers design experiments to investigate CASTOR3's potential role in amino acid sensing?

To investigate CASTOR3's role in amino acid sensing, particularly arginine sensing, researchers should design experiments that parallel established protocols for CASTOR1/2:

• Amino Acid Binding Assays:

  • Express and purify recombinant CASTOR3 protein

  • Perform equilibrium binding assays with radiolabeled amino acids (particularly arginine)

  • Determine binding affinity and specificity through competition experiments

• Protein-Protein Interaction Studies:

  • Investigate CASTOR3 interaction with GATOR2 components under various amino acid conditions

  • Perform co-immunoprecipitation after amino acid starvation and repletion

  • Use proximity ligation assays to visualize interactions in situ

• Functional Impact on mTORC1 Signaling:

  • Generate CASTOR3 knockdown and overexpression cell lines

  • Monitor mTORC1 activity (phosphorylation of S6K, 4E-BP1) in response to amino acid availability

  • Compare responses in wild-type versus CASTOR3-modulated cells

• Structure-Function Analysis:

  • Create CASTOR3 mutants based on key residues identified in CASTOR1 (e.g., equivalent to I280 in CASTOR1)

  • Test these mutants for amino acid binding and GATOR2 interaction

  • Assess their impact on mTORC1 signaling

These experimental approaches would help determine whether CASTOR3 functions similarly to CASTOR1 as an arginine sensor or has distinct sensing properties.

What methodological considerations are important when using CASTOR3 Antibody for quantitative protein analysis?

When using CASTOR3 Antibody for quantitative protein analysis:

• Sample Preparation:

  • Standardize protein extraction methods across all samples

  • Determine optimal lysis buffer composition (e.g., RIPA or NP-40 buffer with protease inhibitors)

  • Quantify total protein using reliable methods (BCA or Bradford assay)

• Western Blot Optimization:

  • Determine linear dynamic range for CASTOR3 detection

  • Optimize antibody concentration (typically start with 1:2000 dilution)

  • Select appropriate loading controls (β-actin, GAPDH, or total protein normalization)

• ELISA Considerations:

  • Follow recommended dilutions (1:2000-1:10000)

  • Generate standard curves using recombinant CASTOR3 protein

  • Include technical replicates (minimum triplicate) for each sample

  • Validate with spike-recovery experiments

• Data Analysis:

  • Use appropriate normalization strategies

  • Apply statistical methods suitable for the experimental design

  • Consider biological variation when interpreting results

• Validation Approaches:

  • Confirm specificity with knockout/knockdown controls

  • Verify results using alternative antibodies or detection methods

  • Consider absolute quantification using mass spectrometry-based approaches

Careful optimization and validation are essential for generating reliable quantitative data on CASTOR3 expression levels.

What are common issues with CASTOR3 Antibody in western blotting and how can they be resolved?

Researchers may encounter several challenges when using CASTOR3 Antibody for western blotting:

• Weak or No Signal:

  • Increase antibody concentration (try 1:500 instead of 1:2000)

  • Extend primary antibody incubation (overnight at 4°C)

  • Enhance detection sensitivity with amplification systems

  • Verify protein expression in your sample type

  • Check transfer efficiency with reversible staining

• High Background:

  • Increase blocking time/concentration (5% BSA or milk for 2 hours)

  • Use more stringent washing (add 0.1% SDS to TBST wash buffer)

  • Decrease antibody concentration

  • Try alternative blocking agents (casein, commercial blockers)

  • Filter antibody solution before use

• Non-specific Bands:

  • Use gradient gels for better separation

  • Optimize sample preparation (add phosphatase inhibitors)

  • Pre-adsorb antibody with cell lysates from CASTOR3 knockout cells

  • Confirm specificity with peptide competition experiments

  • Consider using monoclonal antibodies for higher specificity

• Inconsistent Results:

  • Standardize protein extraction and quantification methods

  • Prepare fresh buffers and reagents

  • Maintain consistent incubation times and temperatures

  • Use internal loading controls rigorously

  • Consider using automated western blot systems for enhanced reproducibility

These troubleshooting strategies should help optimize CASTOR3 detection in western blotting applications.

How can researchers interpret contradictory data regarding CASTOR3 localization or function?

When faced with contradictory data regarding CASTOR3:

• Methodological Differences:

  • Compare antibody clones, sources, and validation methods

  • Examine fixation and permeabilization protocols that might affect epitope accessibility

  • Consider differences in detection systems and sensitivity

• Biological Variability:

  • Assess cell type-specific expression and regulation

  • Examine effects of cell confluence, passage number, and culture conditions

  • Consider potential post-translational modifications affecting detection

• Resolution Strategies:

  • Use multiple antibodies targeting different CASTOR3 epitopes

  • Employ complementary techniques (IF, IHC, fractionation, mass spectrometry)

  • Validate with genetic approaches (CRISPR knockout, siRNA knockdown)

  • Use tagged CASTOR3 constructs as additional controls

• Functional Assessment:

  • Design experiments to directly test contradictory functional hypotheses

  • Consider context-dependent regulation (nutrient status, stress conditions)

  • Examine potential compensatory mechanisms by other CASTOR proteins

  • Assess pathway regulation through multiple downstream readouts

When interpreting contradictory results, consider that CASTOR family proteins show complex regulation patterns, as observed with CASTOR1 and CASTOR2, which displayed differential effects when overexpressed in cells .

What statistical approaches are most appropriate for analyzing CASTOR3 expression data across different experimental conditions?

For robust statistical analysis of CASTOR3 expression data:

• Exploratory Data Analysis:

  • Check data distribution (normality tests: Shapiro-Wilk or Kolmogorov-Smirnov)

  • Identify outliers (box plots, Dixon's Q test, ROUT method)

  • Assess variance homogeneity (Levene's test, Brown-Forsythe test)

• Statistical Tests for Group Comparisons:

  • For normally distributed data: t-test (two groups) or ANOVA (multiple groups)

  • For non-normally distributed data: Mann-Whitney U (two groups) or Kruskal-Wallis (multiple groups)

  • For paired data: Paired t-test or Wilcoxon signed-rank test

  • Follow with appropriate post-hoc tests (Tukey's, Dunnett's, Bonferroni)

• Multiple Comparison Adjustments:

  • Apply false discovery rate (FDR) correction for multiple comparisons

  • Use Benjamini-Hochberg procedure for controlling FDR

  • Consider family-wise error rate control (Bonferroni, Holm's method)

• Correlation and Regression Analysis:

  • Pearson's or Spearman's correlation for relationship with other variables

  • Multiple regression for identifying predictors of CASTOR3 expression

  • ANCOVA when controlling for covariates

• Reporting Requirements:

  • Include sample sizes, p-values, and effect sizes

  • Report specific statistical tests used with justification

  • Provide confidence intervals when appropriate

  • Present both raw data and derived statistics

These approaches ensure rigorous analysis of CASTOR3 expression data across experimental conditions, facilitating reliable interpretation and reproducibility.

What are promising research avenues for exploring CASTOR3's potential role in disease mechanisms?

Based on known functions of CASTOR family proteins, several promising research directions for CASTOR3 include:

• Cancer Biology:

  • Investigate CASTOR3 expression patterns across cancer types

  • Analyze correlation with patient outcomes and treatment responses

  • Explore role in regulating cancer cell metabolism via mTORC1 pathway

  • Examine potential as a biomarker or therapeutic target

• Metabolic Disorders:

  • Study CASTOR3's potential role in nutrient sensing and metabolic adaptation

  • Investigate involvement in insulin signaling and glucose metabolism

  • Explore connections to obesity, diabetes, and metabolic syndrome

  • Examine tissue-specific functions in metabolic regulation

• Neurodegenerative Diseases:

  • Assess CASTOR3 expression in neuronal tissues and its regulation

  • Investigate potential neuroprotective or neurotoxic effects

  • Examine relationship with protein aggregation and autophagy regulation

  • Study potential links to mTORC1 dysregulation in neurodegeneration

• Immunological Functions:

  • Explore CASTOR3's role in immune cell metabolism and function

  • Investigate impact on T-cell activation and differentiation

  • Study potential involvement in inflammatory responses

  • Examine connections to immunometabolism and disease

These research directions could significantly advance our understanding of CASTOR3's biological significance and potential as a therapeutic target.

How might researchers design experiments to explore the evolution and conservation of CASTOR3 across species?

To investigate evolutionary aspects of CASTOR3:

• Comparative Genomics Approach:

  • Identify CASTOR3 homologs across species using bioinformatics tools

  • Perform phylogenetic analysis to trace evolutionary relationships

  • Analyze selective pressure using dN/dS ratios

  • Identify conserved domains and critical residues

• Structural Biology Studies:

  • Model CASTOR3 structure based on known ACT domain structures

  • Compare with CASTOR1 and CASTOR2 structural features

  • Identify potential amino acid binding pockets

  • Analyze conservation of key structural elements

• Functional Conservation Experiments:

  • Express CASTOR3 orthologs from different species in mammalian cells

  • Assess their capacity to interact with human GATOR2 components

  • Compare amino acid binding properties

  • Evaluate effects on mTORC1 signaling across species

• Evolutionary Biochemistry:

  • Reconstruct ancestral CASTOR proteins

  • Test their biochemical properties and interaction partners

  • Identify key mutations that led to functional diversification

  • Assess potential co-evolution with mTORC1 pathway components

This multi-faceted approach would provide insights into how CASTOR3 evolved within the broader context of nutrient sensing and mTORC1 regulation across species.

What methodological advances would enhance the study of CASTOR3 and its interactions with cellular signaling networks?

Several methodological advances would significantly enhance CASTOR3 research:

• Advanced Protein Interaction Technologies:

  • Proximity labeling approaches (BioID, APEX) to identify CASTOR3 interactome

  • High-throughput yeast two-hybrid or mammalian two-hybrid screening

  • FRET/BRET-based sensors to monitor CASTOR3 interactions in real-time

  • Single-molecule imaging to track CASTOR3 complex formation

• Structural Biology Tools:

  • Cryo-EM to resolve CASTOR3 structure and complexes

  • Hydrogen-deuterium exchange mass spectrometry to map binding interfaces

  • NMR spectroscopy to characterize dynamic protein-protein interactions

  • X-ray crystallography to determine atomic-level structure

• Genetic Engineering Approaches:

  • CRISPR-based endogenous tagging for physiological expression studies

  • Inducible and tissue-specific knockout models

  • Domain-swapping experiments between CASTOR family members

  • Optogenetic or chemogenetic control of CASTOR3 activity

• Systems Biology Integration:

  • Multi-omics approaches combining proteomics, transcriptomics, and metabolomics

  • Mathematical modeling of CASTOR3's role in nutrient sensing networks

  • Network analysis of CASTOR3 interactions under various conditions

  • Machine learning to predict CASTOR3 function from large datasets

These methodological advances would provide deeper insights into CASTOR3's function in complex cellular signaling networks and its potential physiological significance.