RRAGB Antibody

What is RRAGB and what are its primary cellular functions?

RRAGB is a member of the GTR/RAG GTP-binding protein family that plays a critical role in amino acid sensing and mTORC1 pathway regulation. It forms heterodimeric complexes with RagC/RRAGD that cycle between active and inactive forms. In its active form, RRAGB contributes to the recruitment of mTORC1 to lysosomes, where it can be activated by RHEB, thereby influencing nutrient sensing and energy balance within cells . This recruitment process represents a crucial step in the activation of the mTOR signaling cascade by amino acids .

Which applications are RRAGB antibodies suitable for?

RRAGB antibodies are validated for multiple experimental applications:

For optimal results, it's recommended to titrate each antibody in your specific testing system .

What species reactivity can be expected with RRAGB antibodies?

Commercial RRAGB antibodies predominantly show reactivity with human samples, with some cross-reactivity to mouse and rat samples. For example, Proteintech's 13023-1-AP antibody has been validated for both human and mouse reactivity , while Cell Signaling Technology's RagB (D18F3) Rabbit mAb shows reactivity with human and monkey samples . Always check the manufacturer's datasheet for specific reactivity information before designing experiments with different species.

How should I optimize Western blot conditions for RRAGB detection?

For optimal Western blot detection of RRAGB:

• Sample preparation: Effectively lyse cells using RIPA buffer supplemented with protease inhibitors to prevent degradation of RRAGB (observed MW: 40 kDa).

• Gel selection: Use 10-12% SDS-PAGE gels for optimal resolution of the 40 kDa RRAGB protein.

• Antibody dilution: Start with a 1:1000 dilution for primary antibody and adjust based on signal strength. Incubate overnight at 4°C for best results .

• Positive controls: Include HEK-293T cell lysate as a positive control, as shown in validation data from multiple antibodies .

• Loading control: Use housekeeping proteins like GAPDH or β-actin for normalization.

Remember that non-specific bands may appear; verify the RRAGB band identity using knockdown/knockout samples when possible .

What are the best immunoprecipitation conditions for studying RRAGB interactions?

For effective immunoprecipitation of RRAGB:

• Antibody selection: Choose antibodies specifically validated for IP applications, such as Cell Signaling Technology's RagB (D18F3) Rabbit mAb or Proteintech's 13023-1-AP .

• Lysate preparation: Prepare fresh cell lysates using NP-40 or RIPA buffer containing phosphatase and protease inhibitors. Use 1-3 mg of total protein lysate per IP reaction.

• Antibody amount: Use 0.5-4.0 μg of antibody per IP reaction, with 6 μg showing good results in published protocols .

• Controls: Always include an isotype-matched IgG control to identify non-specific binding.

• Detection method: For Western blot detection post-IP, use chemiluminescence with appropriate exposure times (published data suggests 3 minutes as effective) .

This approach is particularly valuable for studying RRAGB interactions with other Rag family proteins and components of the mTORC1 signaling pathway .

How can I interpret RRAGB expression patterns in relation to disease progression?

When analyzing RRAGB expression data:

A multivariate approach incorporating these factors can provide more robust interpretations than single-parameter analysis.

What statistical methods are appropriate for analyzing RRAGB expression in relation to immune infiltration?

For analyzing relationships between RRAGB expression and immune parameters:

• Correlation methods:

  • Use Spearman's method for correlation with tumor immune infiltration (B cells, CD4+ T cells, macrophages)

  • Use Pearson's method for correlation with ImmuneScore and StromalScore

• Wilcoxon tests: Apply Wilcoxon rank-sum test for analyzing associations between tumor immune infiltration levels and different somatic copy number alterations for RRAGB .

• Regression models: Employ univariate and multivariate Cox regression analyses to evaluate RRAGB as an independent prognostic factor (both p < 0.05 in published studies) .

• Enrichment analysis: Use Gene Set Enrichment Analysis (GSEA) to identify signaling pathways associated with high RRAGB expression phenotypes .

Remember to adjust for multiple testing when analyzing relationships with multiple immune markers simultaneously.

How does the RRAGB-RagC interaction affect mTORC1 signaling during amino acid starvation?

The RRAGB-RagC heterodimer plays a critical role in mTORC1 regulation under varying nutrient conditions:

• Cycling mechanism: The heterodimer cycles between active and inactive forms. When amino acids are available, the complex is in its active form with GTP-bound RRAGB and GDP-bound RagC, promoting mTORC1 recruitment to lysosomes .

• TSC recruitment: Under amino acid limitation, the Rag GTPase in its RAGA GDP:RAGC GTP form recruits the TORC1 inhibitor TSC to lysosomal membranes, inhibiting mTORC1 activity .

• GATOR2 involvement: In the absence of the GATOR2 complex, knocking down components of the Rag GTPase prevents the recruitment of TSC to lysosomes, potentially allowing TORC1 to bind directly to its activator Rheb .

• Dynamic behavior: TSC shuttles on and off lysosomes in response to multiple stimuli. In certain cell lines like HeLa, lysosomes retain a pool of TSC even under growth-favorable conditions .

To study this interaction experimentally, consider using fluorescently tagged RRAGB and RagC to monitor their subcellular localization and interaction dynamics in response to amino acid availability. Protein proximity assays like FRET or PLA could also provide valuable insights into the spatial and temporal dynamics of these interactions.

What role does RRAGB play in immune response regulation and how might this impact cancer immunotherapy approaches?

RRAGB has significant associations with immune parameters that could influence immunotherapy strategies:

• Immune checkpoint correlation: RRAGB mRNA expression shows significant associations with multiple immune checkpoint molecules including TNFSF4, TNFSF9, TNFSF18, TMIGD2, TNFRSF14, and TNFRSF18 in colon adenocarcinoma (all p < 0.05) .

• Immune cell pathways: RRAGB expression is markedly related to various immune cell populations, including Type 17 T helper cells, Type 2 T helper cells, neutrophils, monocytes, memory B cells, CD56dim natural killer cells, and activated dendritic cells .

• Mismatch repair genes: RRAGB shows significant links to mismatch repair genes MLH1, MSH2, MSH6, PMS2, and EPCAM in COAD (all p < 0.001), suggesting potential relationships with microsatellite instability, a biomarker for immunotherapy response .

• B and T cell infiltration: RRAGB mRNA expression correlates with B cells, CD4+ T cells, and macrophage cell infiltration (all p < 0.05) .

When designing immunotherapy studies, consider stratifying patients based on RRAGB expression levels and analyzing response rates within these subgroups. Additionally, combination approaches targeting both RRAGB-related pathways and immune checkpoints might enhance therapeutic efficacy.

How can multiplex imaging be optimized to simultaneously detect RRAGB and other mTOR pathway components?

For multiplex detection of RRAGB and related proteins:

• Antibody panel design:

  • Select antibodies raised in different host species to avoid cross-reactivity

  • Include key mTOR pathway components: RRAGB, RRAGC, Raptor, mTOR, and RHEB

  • Validate each antibody individually before multiplex experiments

• Spectral unmixing optimization:

  • Use fluorophores with minimal spectral overlap

  • Include single-stained controls for accurate spectral unmixing

  • Consider tyramide signal amplification for low-abundance proteins

• Sequential staining protocol:

  • Start with heat-induced epitope retrieval using TE buffer pH 9.0 as recommended for RRAGB antibodies

  • Apply antibodies sequentially with microwave treatment between rounds to remove previous antibodies

  • Include DAPI for nuclear counterstaining

• Image analysis strategy:

  • Use cell segmentation algorithms to define cellular/subcellular compartments

  • Quantify co-localization between RRAGB and other pathway components

  • Analyze relative distances between proteins under different experimental conditions

This approach enables simultaneous visualization of multiple pathway components and their subcellular localization in response to experimental manipulations of amino acid availability or growth factor signaling.

What are the best methods for studying RRAGB dynamics in response to amino acid availability?

To study dynamic RRAGB responses to amino acid availability:

• Live cell imaging approaches:

  • Generate stable cell lines expressing fluorescently-tagged RRAGB (e.g., RRAGB-GFP)

  • Use spinning disk confocal microscopy for rapid acquisition with minimal phototoxicity

  • Employ lysosomal markers (LAMP1-RFP) to monitor RRAGB translocation to lysosomes

• Acute manipulation protocols:

  • Rapidly switch between amino acid-rich and amino acid-free media using perfusion systems

  • Monitor RRAGB localization at 1-minute intervals for up to 30 minutes

  • Quantify cytoplasmic-to-lysosomal ratio of RRAGB fluorescence intensity over time

• Biochemical fractionation:

  • Separate cytosolic and lysosomal fractions at defined timepoints after amino acid withdrawal

  • Perform Western blot analysis with RRAGB antibodies (1:1000 dilution)

  • Include markers for cytosolic (GAPDH) and lysosomal (LAMP1) fractions

• Proximity labeling approaches:

  • Use BioID or APEX2 fused to RRAGB to identify dynamic interactors

  • Perform time-course experiments following amino acid manipulation

  • Analyze biotinylated proteins by mass spectrometry

These methodologies provide complementary information about the spatial and temporal dynamics of RRAGB in response to nutrient availability.

How can discrepancies between RRAGB antibody detection methods be reconciled in research findings?

When facing discrepancies between RRAGB detection methods:

• Antibody epitope analysis:

  • Compare epitope regions of different antibodies (e.g., N-terminal vs. C-terminal)

  • Consider potential post-translational modifications that might mask epitopes

  • Review immunogen information (e.g., Proteintech's 13023-1-AP uses a fusion protein antigen)

• Validation approaches:

  • Perform siRNA/shRNA knockdown of RRAGB to confirm specificity

  • Use CRISPR-Cas9 knockout samples as negative controls

  • Compare multiple antibodies targeting different epitopes

• Application-specific optimizations:

  • For IHC: Test different antigen retrieval methods (TE buffer pH 9.0 vs. citrate buffer pH 6.0)

  • For WB: Compare reducing vs. non-reducing conditions

  • For IP: Test different lysis buffers (RIPA vs. NP-40)

• Standardization of quantification:

  • Use recombinant RRAGB protein as a standard curve

  • Apply consistent image analysis methods across experiments

  • Report relative rather than absolute values when comparing between methods

This systematic approach helps identify the source of discrepancies and establish reliable protocols for consistent RRAGB detection across different experimental platforms.

What are the most effective strategies for studying RRAGB mutations and their functional consequences?

To effectively investigate RRAGB mutations:

• Mutation identification and selection:

  • Analyze cancer genomics databases (TCGA, cBioPortal) for recurrent RRAGB mutations

  • Focus on mutations in functional domains (GTP-binding, RagC interaction)

  • Prioritize mutations with clinical correlations (e.g., those associated with survival differences)

• Expression systems:

  • Generate expression constructs for wild-type and mutant RRAGB

  • Use inducible expression systems to control expression levels

  • Include epitope tags (HA, FLAG) that don't interfere with function

• Functional assays:

  • GTP binding assay: Compare GTP loading capacity of wild-type vs. mutant RRAGB

  • Heterodimer formation: Assess interaction with RagC using co-immunoprecipitation

  • mTORC1 activation: Monitor phosphorylation of S6K and 4E-BP1

  • Subcellular localization: Examine recruitment to lysosomes using confocal microscopy

• CRISPR-based approaches:

  • Generate RRAGB knockout cell lines for complementation studies

  • Introduce specific mutations using homology-directed repair

  • Create knock-in reporter cell lines for endogenous mutation studies

• In vivo models:

  • Generate tissue-specific RRAGB mutant mouse models

  • Analyze phenotypes related to mTORC1 signaling (growth, metabolism)

  • Test therapeutic interventions targeting mutant-specific vulnerabilities

This integrated approach provides comprehensive insights into how RRAGB mutations affect protein function and cellular physiology, potentially identifying new therapeutic opportunities.

How can RRAGB be targeted in cancer therapy development?

Based on current research, several strategies for targeting RRAGB in cancer therapy show promise:

• Small molecule inhibitors:

  • Design compounds that interfere with RRAGB-RagC heterodimer formation

  • Develop inhibitors that lock RRAGB in its GDP-bound state, preventing mTORC1 activation

  • Create molecules that disrupt RRAGB interaction with raptor

• Therapeutic rationale:

  • RRAGB serves as an independent prognostic factor in colon adenocarcinoma

  • High RRAGB expression correlates with poor prognosis in COAD patients (p < 0.05)

  • RRAGB is linked to microsatellite instability (MSI) and tumor mutational burden (TMB)

• Combinatorial approaches:

  • Combine RRAGB-targeting therapies with mTOR inhibitors for synergistic effects

  • Pair with immune checkpoint inhibitors based on RRAGB's associations with immune parameters

  • Consider stratification based on RRAGB expression levels for personalized treatment strategies

• Biomarker application:

  • Use RRAGB expression as a companion diagnostic for therapy selection

  • Develop RRAGB-based nomograms for patient stratification

  • Monitor RRAGB as a marker of treatment response

As research progresses, understanding RRAGB's role in different cancer types will further refine these therapeutic approaches and potentially reveal new intervention opportunities.

What are the emerging technologies for studying RRAGB protein interactions and dynamics?

Cutting-edge technologies for investigating RRAGB interactions include:

• Proximity labeling methods:

  • BioID or TurboID fused to RRAGB to identify proximal proteins in living cells

  • APEX2-based approaches for temporal resolution of interaction dynamics

  • Split-BioID for detecting specific protein-protein interactions in situ

• Advanced microscopy techniques:

  • Super-resolution microscopy (STORM, PALM) to visualize nanoscale organization

  • Lattice light-sheet microscopy for high-speed 3D imaging of RRAGB dynamics

  • FRET/FLIM for real-time monitoring of RRAGB-partner interactions

• Protein structure determination:

  • Cryo-EM analysis of the RRAGB-RagC heterodimer in different nucleotide-bound states

  • AlphaFold2 predictions to guide mutagenesis and interaction studies

  • Hydrogen-deuterium exchange mass spectrometry to map interaction interfaces

• Single-molecule approaches:

  • Single-molecule tracking to monitor RRAGB diffusion and binding kinetics

  • Optical tweezers to measure forces in RRAGB-partner interactions

  • NanoBiT complementation assays for real-time interaction monitoring

• Multi-omics integration:

  • Combine proteomics, transcriptomics, and metabolomics to build comprehensive models

  • Correlate RRAGB interactome changes with metabolic alterations

  • Apply machine learning to predict RRAGB interaction dynamics under varying conditions