ARL4A Antibody

What is ARL4A and why is it significant for research?

ARL4A belongs to the ADP-ribosylation factor/ARF-like protein family of GTPases. It cycles between inactive GDP-bound and active GTP-bound forms, with this cycling regulated by guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs). ARL4A has significant research importance due to its roles in recruiting CYTH family proteins to the plasma membrane, regulating endosomal trafficking, and potentially functioning as a prognostic biomarker in cancer . It contains nuclear localization signals (NLSs) at its C-terminus and is found at the plasma membrane, nucleus, and cytoplasm, making it relevant for studies involving multiple cellular compartments .

How should I select an appropriate ARL4A antibody for my research?

When selecting an ARL4A antibody, consider these critical factors:

• Target epitope: Antibodies targeting different regions (N-terminal, C-terminal, or specific domains) may yield different results

• Host species: Choose based on compatibility with your experimental system

• Clonality: Polyclonal antibodies offer broader epitope recognition while monoclonals provide greater specificity

• Applications validated: Ensure the antibody is validated for your specific application (IHC, IF, WB, ELISA)

• Species reactivity: Verify cross-reactivity with your species of interest (human, mouse, rat)

Most commercial ARL4A antibodies are rabbit polyclonal antibodies reactive to human, mouse, and rat samples, suitable for applications including immunohistochemistry (1:50-1:200 dilution), immunofluorescence (1:50-1:200 dilution), and Western blotting .

What are the recommended protocols for antibody validation?

To validate an ARL4A antibody:

• Perform Western blotting on:

  • Positive controls (tissues known to express ARL4A like liver or testis)

  • Negative controls using siRNA knockdown or CRISPR knockout of ARL4A

  • Multiple cell lines to assess cross-reactivity

• Conduct specificity tests:

  • Pre-absorption with immunizing peptide

  • Comparison with different antibodies against the same target

  • Immunoprecipitation followed by mass spectrometry

• Application-specific validation:

  • For IHC/IF: Include appropriate positive and negative tissue controls

  • Include isotype controls to assess non-specific binding

A successful validation should show the expected molecular weight band (~20 kDa) for ARL4A in Western blot and specific cellular localization patterns in immunofluorescence/immunohistochemistry.

What are the optimal storage and handling conditions for ARL4A antibodies?

For maximum antibody performance and longevity:

Most commercial ARL4A antibodies are supplied in Phosphate Buffered Saline (pH 7.3) with additives for stability . Follow manufacturer guidelines for specific products, as formulations may vary.

How can I use ARL4A antibodies to study endosomal trafficking pathways?

ARL4A plays a critical role in endosomal trafficking, particularly affecting EGFR degradation. To investigate this:

• Track receptor trafficking using dual immunofluorescence:

  • Co-stain with ARL4A antibody and markers for early endosomes (EEA1) or late endosomes/lysosomes (Lamp1)

  • Monitor trafficking of internalized receptors at various time points after stimulation

• Assess endosomal dynamics:

  • Use fluorescently labeled ligands (e.g., EGF-Alexa-555) to track receptor internalization

  • Compare trafficking kinetics between control and ARL4A-depleted cells

  • Quantify colocalization between ARL4A, receptors, and endosomal markers

• Evaluate receptor degradation:

  • Manipulate ARL4A levels (siRNA knockdown or overexpression)

  • Measure receptor half-life using cycloheximide chase assays

  • Apply lysosomal inhibitors (NH4Cl) or proteasome inhibitors (MG132) to determine degradation pathways

Research has shown that ARL4A depletion accelerates EGFR lysosomal degradation, with increased colocalization with EEA1 at early time points and Lamp1 at later time points post-stimulation .

What role does ARL4A play in cancer biology and how can antibodies help investigate this?

ARL4A has emerging significance in cancer biology, particularly in thyroid cancer:

• Expression analysis in tumors:

  • Use IHC with ARL4A antibodies to assess expression levels in tumor vs. normal tissues

  • Correlate expression with clinicopathological parameters and patient outcomes

• Immune microenvironment studies:

  • Perform multiplex immunofluorescence with ARL4A and immune cell markers

  • Analyze the relationship between ARL4A expression and immune cell infiltration

• Mechanistic investigations:

  • Examine downstream signaling pathways affected by ARL4A manipulation

  • Study effects on cancer cell proliferation, migration, and invasion

Recent research has shown that elevated ARL4A expression correlates with poor prognosis in thyroid cancer patients. Furthermore, ARL4A expression negatively correlates with immune cell infiltration, including CD4+ T cells, macrophages, neutrophils, CD8+ T cells, and dendritic cells .

How can I investigate ARL4A's protein-protein interactions?

To study ARL4A's interactions with other proteins:

• Co-immunoprecipitation:

  • Use ARL4A antibodies to pull down protein complexes

  • Analyze by Western blot or mass spectrometry to identify interacting partners

• Proximity ligation assays:

  • Detect in situ protein interactions with <40nm proximity

  • Provides spatial context for interactions within cells

• FRET/BRET analysis:

  • Measure energy transfer between fluorophore-tagged proteins

  • Quantify real-time interactions in living cells

• Yeast two-hybrid screening:

  • Identify novel interaction partners

  • Map interacting domains and critical residues

Research has identified interactions between ARL4A and proteins like Robo1, where residues 1394-1398 of Robo1 are critical for this interaction. These studies employed yeast two-hybrid screens, GST pull-down assays, and co-immunoprecipitation to characterize the interaction .

What approaches can be used to study the relationship between ARL4A and immune cell function?

Based on ARL4A's correlation with immune infiltration in cancer:

• Immune cell profiling:

  • Use flow cytometry to quantify immune cell populations in ARL4A-manipulated systems

  • Apply single-cell RNA sequencing to identify immune cell subtypes affected by ARL4A

• Functional assays:

  • Assess immune cell migration, activation, and cytokine production

  • Co-culture experiments with ARL4A-modified cancer cells and immune cells

• In vivo models:

  • Compare immune infiltration in ARL4A knockout vs. wild-type animals

  • Evaluate responses to immunotherapy in contexts of varying ARL4A expression

Studies have shown that ARL4A expression negatively correlates with 14 of 24 immune cell types analyzed in thyroid cancer. High ARL4A expression is associated with a reduction in activated dendritic cells, B cells, cytotoxic cells, dendritic cells, macrophages, and T cells .

How does the GTP-binding state of ARL4A affect its function and localization?

To investigate ARL4A's GTP-dependent functions:

• Generate and study GTP-binding mutants:

  • Create GTP-binding defective mutants (e.g., T35N equivalent)

  • Develop GTP-hydrolysis defective mutants (e.g., Q71L equivalent)

• Analyze subcellular localization:

  • Compare wild-type and mutant localization using immunofluorescence

  • Perform subcellular fractionation followed by Western blotting

  • Assess changes in localization upon cellular stimulation

• Functional consequences:

  • Examine effects on interacting partners and downstream pathways

  • Measure cellular processes known to be regulated by ARL4A

Research on the related protein ARL4D shows that GTP-binding-defective ARL4D(T35N) localizes to mitochondria and affects mitochondrial morphology and membrane potential. The N-terminal myristoylation of ARL4D is required for this mitochondrial localization .

What are the optimal conditions for immunohistochemistry with ARL4A antibodies?

For successful IHC staining:

For frozen sections, 10-minute fixation in cold acetone or 4% paraformaldehyde is effective before proceeding with standard immunostaining protocols .

How can I troubleshoot issues with Western blotting using ARL4A antibodies?

When encountering Western blot problems:

• No signal:

  • Verify protein expression in your sample (ARL4A is abundant in liver and testis)

  • Test antibody on known positive control lysates

  • Increase antibody concentration or incubation time

  • Check transfer efficiency and blocking conditions

• Multiple bands:

  • Optimize sample preparation to reduce protein degradation

  • Use freshly prepared samples with protease inhibitors

  • Verify antibody specificity with blocking peptides

  • Consider post-translational modifications of ARL4A

• High background:

  • Increase washing steps (duration/frequency)

  • Optimize blocking (5% BSA often works better than milk for phospho-specific antibodies)

  • Reduce antibody concentration

  • Use more specific secondary antibodies

What experimental design considerations are important when studying ARL4A in cancer models?

When investigating ARL4A in cancer:

• Model selection:

  • Cell lines: Choose lines with varying baseline ARL4A expression

  • Animal models: Consider genetically engineered models with ARL4A alterations

  • Patient samples: Include diverse stages and subtypes

• Expression manipulation:

  • siRNA/shRNA for transient/stable knockdown

  • CRISPR/Cas9 for complete knockout

  • Overexpression of wild-type or mutant forms

• Analytical approaches:

  • Correlate ARL4A levels with clinical parameters

  • Assess impact on cancer hallmarks (proliferation, invasion, etc.)

  • Examine effects on therapy response

• Controls and validation:

  • Include multiple independently derived cell clones

  • Validate findings across multiple model systems

  • Confirm antibody specificity in each model system

How can I use advanced imaging techniques with ARL4A antibodies?

For sophisticated imaging applications:

• Super-resolution microscopy:

  • STED, PALM, or STORM imaging for nanoscale localization

  • Requires highly specific antibodies and appropriate fluorophores

• Live-cell imaging:

  • Generate fluorescent protein-tagged ARL4A constructs

  • Monitor trafficking and localization in real-time

  • Apply FRAP (Fluorescence Recovery After Photobleaching) to study dynamics

• Correlative light-electron microscopy (CLEM):

  • Combine immunofluorescence with ultrastructural analysis

  • Localize ARL4A to specific subcellular compartments at nanometer resolution

• Quantitative analysis:

  • Apply appropriate software for colocalization analysis

  • Measure Pearson's or Mander's coefficients for objective assessment

  • Use machine learning approaches for pattern recognition

How is ARL4A being investigated as a potential biomarker or therapeutic target?

Current research directions include:

• Diagnostic/prognostic biomarker development:

  • Validation in multiple cancer types and cohorts

  • Integration with other biomarkers for improved prediction

  • Development of standardized IHC protocols for clinical use

• Therapeutic targeting strategies:

  • Small molecule inhibitors of ARL4A GTPase activity

  • Disruption of specific protein-protein interactions

  • Combination with immunotherapies based on immune correlations

• Mechanistic investigations:

  • Pathway analysis to identify downstream effectors

  • Systems biology approaches to map ARL4A networks

  • Structure-function studies to guide targeted drug design

What are the latest methodologies for studying ARL4A in the context of active learning approaches?

Active learning approaches for ARL4A research:

• Library-on-library screening:

  • Apply antibody arrays against antigen libraries

  • Identify specific binding pairs and interaction parameters

• Machine learning integration:

  • Develop predictive models for ARL4A binding specificity

  • Improve out-of-distribution predictions for novel interactions

• Iterative labeling strategies:

  • Start with small labeled datasets and expand based on model uncertainty

  • Reduce experimental costs while maximizing information gain

Recent research has shown that active learning strategies can reduce the number of required experimental samples by up to 35% and accelerate the learning process compared to random sampling approaches .