RHOF Antibody

What is RHOF and what biological functions does it regulate?

RHOF (also known as Rif or ARHF) is a plasma membrane-associated small GTPase that cycles between active GTP-bound and inactive GDP-bound states. It functions as a key regulator of cytoskeletal dynamics, specifically causing the formation of thin, actin-rich surface projections called filopodia . RHOF works cooperatively with CDC42 and Rac to generate additional cytoskeletal structures, increasing the diversity of actin-based morphology .

RHOF has multiple biological functions including:

• Regulation of filopodium remodeling through mDia2 interaction

• Involvement in axonogenesis and cell adhesion

• Acting as a master regulator in cytoskeletal reorganization and membrane trafficking

• Modulation of immunological functions, particularly in B cell development

RHOF expression is notably high in tissues such as brain and testis, where it interacts with various effector proteins to carry out its specialized functions .

How do I select the appropriate RHOF antibody for my research application?

Selecting the appropriate RHOF antibody depends on several key experimental considerations:

Application compatibility:

• For Western blotting: Most RHOF antibodies are validated for this application

• For immunohistochemistry: Select antibodies specifically validated for IHC-P like ab155149

• For flow cytometry: Consider antibodies like ab201976 (mouse monoclonal)

• For immunofluorescence: Look for antibodies validated for IF like the rabbit polyclonal from Proteintech

Species reactivity:

• For human samples: All examined antibodies react with human RHOF

• For mouse/rat studies: Select antibodies with confirmed cross-reactivity like ab224555 or Proteintech's 12290-1-AP

Antibody format:

• Monoclonal antibodies (e.g., ab201976) offer high reproducibility and specificity for epitopes

• Polyclonal antibodies (e.g., ab101349) provide broader epitope recognition

Immunogen information:

• For N-terminal targeting: antibodies like ab201976 target aa 1-100

• For broader protein detection: antibodies like ab101349 target aa 1-200

Compare validation data provided by manufacturers, particularly Western blot images showing detection at the expected molecular weight (~24 kDa) .

What methods should I use to validate an RHOF antibody for my specific experimental system?

Antibody validation is critical to ensure reliable research outcomes. For RHOF antibodies, employ these complementary validation approaches:

Western blot validation:

• Run protein lysates from tissues known to express RHOF (brain, testis)

• Confirm detection of a single band at the expected molecular weight (~24 kDa)

• Include multiple control cell lines (e.g., COLO 320, A549, HeLa)

Positive and negative controls:

• Positive controls: Cell lines with known RHOF expression (U87-MG, COLO 320)

• Negative controls: Consider RHOF knockout models or RHOF-null cell lines

• siRNA/shRNA knockdown: Validate specificity by RHOF knockdown, as demonstrated in THP-1 and MOLM-13 AML cells

Orthogonal validation:

• Compare results using antibodies targeting different epitopes of RHOF

• Validate with complementary techniques (e.g., mass spectrometry, RNA-seq data)

Blocking peptide experiments:

• Incubate the antibody with excess RHOF immunogen peptide

• Confirm elimination of specific staining when using the blocked antibody

As described in antibody validation literature, a validated antibody must be shown to be "specific, selective, and reproducible in the context for which it is to be used" . Document all validation steps methodically for future reference and reproducibility.

How can I troubleshoot non-specific binding or high background when using RHOF antibodies?

Non-specific binding is a common challenge with antibodies. For RHOF antibodies specifically:

Optimize antibody dilution:

• Start with manufacturer's recommended dilution (e.g., 1:500 for Western blot with ab101349)

• Perform titration experiments to determine optimal concentration

• For IHC applications, dilutions of 1:20-1:200 may be appropriate

Improve blocking procedures:

• Extend blocking time with 5% BSA or 5% non-fat dry milk

• Consider alternative blocking agents if background persists

• For immunofluorescence, include 0.1% sodium azide in PBS for blocking buffer

Reduce cross-reactivity:

• Pre-adsorb antibody with tissues/cells lacking RHOF expression

• Use species-specific secondary antibodies to minimize cross-reactivity

• Include anti-CD16/32 antibody when working with immune cells to block Fc receptors

Optimize antigen retrieval for IHC:

• Test both citrate buffer (pH 6.0) and TE buffer (pH 9.0) for optimal epitope exposure

• Adjust retrieval time and temperature if needed

Control for tissue auto-fluorescence:

• Include unstained controls to identify auto-fluorescence

• Consider Sudan Black B treatment to reduce auto-fluorescence in tissue sections

For Western blot applications specifically, adding 0.05% Tween-20 to wash buffers and using freshly prepared reagents can significantly reduce background issues.

How should I design experiments to study RHOF expression in different cancer types?

RHOF has been implicated in various cancer types, including AML, pancreatic cancer, hepatocellular carcinoma, and breast cancer . When designing experiments to study RHOF expression:

Tissue panel screening:

• Include multiple cancer types alongside matched normal tissues

• Use validated antibodies like Proteintech's 12290-1-AP for IHC applications

• Quantify expression levels using digital image analysis for objective comparison

Clinical correlation studies:

• Correlate RHOF expression with patient survival data as demonstrated in AML studies

• Analyze expression in relation to clinical parameters (stage, grade, treatment response)

• Compare expression between newly diagnosed, relapsed/refractory, and complete remission cases

Cell type-specific analyses:

• In hematological malignancies, analyze expression in sorted cell populations (e.g., CD34+ vs. CD34-)

• For solid tumors, use dual IHC/IF to correlate RHOF with cell type-specific markers

Experimental methodology:

• Extract RNA and protein from patient samples and cell lines

• Perform RT-qPCR for mRNA quantification

• Use Western blotting with validated antibodies for protein expression

• Complement with IHC on tissue microarrays for spatial context

Data representation:

As demonstrated in AML research, RHOF expression was highest in relapsed/refractory patients compared to newly diagnosed or complete remission cases, suggesting its potential as a prognostic biomarker .

What are the optimal protocols for detecting RHOF in primary immune cells using immunofluorescence?

Detecting RHOF in primary immune cells requires careful optimization due to their relatively small size and potential for non-specific binding:

Sample preparation:

• Isolate primary cells (e.g., B cells, T cells, NK cells) from spleen or blood using appropriate isolation kits

• For adherent staining: Coat slides with poly-L-lysine (0.01%) for better cell attachment

• Fix cells with 4% paraformaldehyde for 10 minutes at room temperature

• Permeabilize with 0.1% Triton X-100 for 5 minutes

Blocking and antibody incubation:

• Block with 5% FCS/0.1% sodium azide/PBS for 30 minutes

• Incubate with anti-RHOF antibody (recommend Proteintech 12290-1-AP at 1:100 dilution)

• Co-stain with lymphocyte subset markers (e.g., B220 for B cells, TCRβ for T cells)

• Include DAPI or 7AAD for nuclear counterstaining

Controls and validation:

• Use RHOF knockout cells or tissues as negative controls

• Include isotype control antibodies to assess non-specific binding

• For B cell subsets, consider co-staining with CD21/CD23 to identify marginal zone B cells

Confocal microscopy settings:

• Use high NA objectives (1.3-1.4) for optimal resolution

• Adjust detector gain to avoid saturation

• Capture Z-stacks to fully visualize subcellular localization

As RHOF is involved in filopodia formation, pay particular attention to membrane protrusions and cytoskeletal structures. In B cells specifically, RHOF has been shown to be crucial for marginal zone B cell development .

How can I investigate the role of RHOF in chemoresistance mechanisms in acute myeloid leukemia?

Recent research has demonstrated RHOF's significant role in AML progression and chemotherapy resistance . To investigate this:

Gain and loss-of-function approaches:

• Generate stable RHOF knockdown cells using shRNA (as demonstrated in THP-1 and MOLM-13 AML cell lines)

• Create RHOF-overexpressing cells using lentiviral expression systems

• Use CRISPR/Cas9 for complete knockout studies

Chemosensitivity assessment:

• Treat control and RHOF-modulated cells with standard chemotherapeutics (Ara-C, idarubicin)

• Assess cell viability, apoptosis (Annexin V/PI staining), and cell cycle distribution

• Determine IC50 values for different drugs with and without RHOF modulation

Signaling pathway analysis:

• Examine the AKT/β-catenin signaling pathway specifically implicated in RHOF-mediated chemoresistance

• Use Western blotting with phospho-specific antibodies to assess pathway activation

• Apply pathway inhibitors to determine rescue effects

In vivo models:

• Establish xenograft models using AML cells with modulated RHOF expression

• Monitor tumor growth, survival, and response to chemotherapy

• Analyze tissue samples for leukemic infiltration and pathway activation

Research has shown that RHOF knockdown significantly enhances chemosensitivity in AML cells, while overexpression decreases apoptosis following treatment with chemotherapeutic agents . The mechanism appears to involve the AKT/β-catenin signaling pathway, providing a potential therapeutic target.

What are the technical considerations for studying RHOF activation states using antibody-based approaches?

RHOF, like other Rho GTPases, cycles between active (GTP-bound) and inactive (GDP-bound) states . Studying these activation states requires specialized approaches:

GTP-bound RHOF pull-down assays:

• Use GST-fused effector binding domains (e.g., mDia2-RBD) to selectively pull down active RHOF

• Process lysates quickly with GTP-preserving buffers containing MgCl₂

• Detect pulled-down active RHOF using validated anti-RHOF antibodies

• Include positive controls (GTPγS-loaded lysates) and negative controls (GDP-loaded lysates)

Activation state-sensitive antibodies:

• Currently, no commercially available antibodies specifically recognize GTP-bound RHOF

• Consider developing conformation-specific antibodies for direct detection of active RHOF

• Validate using mutagenically locked GTP- or GDP-bound RHOF variants

Proximity ligation assays (PLA):

• Use antibodies against RHOF and known effector proteins (mDia2)

• PLA signal indicates protein-protein interaction, suggesting active RHOF

• Combine with stimulation conditions known to activate RHOF

Fluorescence resonance energy transfer (FRET)-based sensors:

• Construct FRET-based biosensors for real-time RHOF activation monitoring

• Validate sensor response using known RHOF activators

• Use live-cell imaging to monitor activation dynamics

Technical considerations:

• Activation states are transient and labile; rapid sample processing is essential

• Validation should include GTPase-deficient (constitutively active) and dominant-negative RHOF mutants

• Consider subcellular fractionation to assess membrane-associated (potentially active) versus cytosolic RHOF

For comprehensive analysis, combine these approaches with functional assays that assess RHOF-dependent processes such as filopodia formation or actin reorganization.

How can I design experiments to investigate the cross-talk between RHOF and other Rho GTPases in immune cell function?

RHOF functions cooperatively with CDC42 and Rac in generating cytoskeletal structures , suggesting important cross-talk between these GTPases. To investigate this in immune cells:

Co-expression and activation analysis:

• Isolate primary immune cells or use relevant cell lines (THP-1, NK cells, CD8+ T cells)

• Stimulate with appropriate activators (cytokines, receptor ligands)

• Assess activation kinetics of multiple Rho GTPases using pull-down assays

• Use validated antibodies for each GTPase to measure total protein levels

Sequential knockdown/knockout studies:

• Generate single and compound knockdowns of RHOF, Rac1, and CDC42

• Assess phenotypic consequences on:

  • Actin cytoskeleton organization (via phalloidin staining)

  • Immunological synapse formation

  • Cytotoxic granule exocytosis in NK and CD8+ T cells

  • Marginal zone B cell development

Effector competition assays:

• Identify shared downstream effectors (e.g., mDia proteins)

• Perform co-immunoprecipitation experiments with and without GTPase activation

• Use proximity ligation assays to visualize protein interactions in situ

Functional readouts:

• For B cells: Assess development of marginal zone B cells, antigen-specific antibody production

• For NK/CD8+ T cells: Measure cytotoxic activity, granule exocytosis, immunological synapse formation

• For all cells: Quantify migration, adhesion, and filopodia formation

Data integration framework:

This approach will provide insights into how these GTPases coordinate distinct but overlapping pathways in immune cell function and development.

What are the best practices for quantifying RHOF protein levels in tissue samples?

Accurate quantification of RHOF protein in tissues requires standardized approaches:

Western blot quantification:

• Use fresh or quickly frozen tissue samples to preserve protein integrity

• Include recombinant RHOF protein standards for absolute quantification

• Run multiple loading controls (β-actin, GAPDH, total protein stain)

• Use validated RHOF antibodies at optimized dilutions (e.g., 1:500-1:2000)

• Employ digital image analysis with appropriate background subtraction

• Normalize to loading controls and calculate relative expression

Immunohistochemistry quantification:

• Optimize antigen retrieval conditions (test both TE buffer pH 9.0 and citrate buffer pH 6.0)

• Use automated staining platforms for consistency when possible

• Include positive control tissues (brain, testis) on each slide

• Apply digital pathology tools to quantify:

  • Staining intensity (0, 1+, 2+, 3+)

  • Percentage of positive cells

  • H-score (intensity × percentage)

• Ensure blinded assessment by multiple observers

Tissue microarray approach:

• Construct TMAs with multiple cores per case to account for heterogeneity

• Include normal tissue controls on each TMA block

• Stain all TMAs in a single batch to minimize technical variation

• Apply automated image analysis for consistent scoring

Standardization considerations:

• Pre-analytical variables (fixation time, processing methods) significantly impact results

• Document all steps of the workflow for reproducibility

• Consider interlaboratory validation for critical findings

A comprehensive approach combining multiple quantification methods will provide the most reliable assessment of RHOF protein levels in tissue samples.

How should I interpret contradictory results between RHOF mRNA and protein expression data?

Discrepancies between mRNA and protein expression are common in biological research and can be particularly relevant for regulatory proteins like RHOF:

Potential explanations for discrepancies:

• Post-transcriptional regulation:

  • miRNA-mediated repression of RHOF translation

  • RNA-binding proteins affecting mRNA stability or translation efficiency

• Post-translational modifications:

  • Protein stability differences (ubiquitination, proteasomal degradation)

  • Active protein turnover despite high mRNA levels

• Technical considerations:

  • Antibody specificity or sensitivity issues

  • Primer efficiency in qPCR assays

  • Different detection thresholds between methods

Systematic investigation approach:

• Validate both assays independently:

  • Confirm antibody specificity through knockout/knockdown controls

  • Verify primer specificity through sequencing of PCR products

• Examine temporal dynamics:

  • Perform time-course experiments to detect potential delays between mRNA and protein expression

  • Consider pulse-chase experiments to assess protein stability

• Investigate regulatory mechanisms:

  • Use proteasome inhibitors to assess protein degradation rates

  • Apply translation inhibitors to examine protein synthesis

  • Test for presence of regulatory miRNAs targeting RHOF

• Reconcile with functional data:

  • Correlate functional outcomes with either mRNA or protein levels

  • Determine which measurement better predicts biological effects

What emerging technologies could enhance the study of RHOF localization and dynamics?

Several cutting-edge technologies can significantly advance our understanding of RHOF biology:

Proximity labeling approaches:

• APEX2 or BioID fused to RHOF to identify proximal interacting proteins

• TurboID for rapid biotin labeling of the RHOF interactome

• Split-BioID for detecting conditional interactions with known partners

Super-resolution microscopy:

• STORM/PALM imaging to visualize RHOF localization beyond diffraction limit

• Lattice light-sheet microscopy for dynamic 3D imaging of RHOF in living cells

• Expansion microscopy to physically enlarge specimens for enhanced resolution

Live-cell biosensors:

• FRET-based sensors for RHOF activation states

• Fluorescent protein-tagged RHOF with minimal functional interference

• Optogenetic tools for spatiotemporal control of RHOF activity

Single-cell proteomics:

• Mass cytometry (CyTOF) with metal-tagged antibodies for multiplexed detection

• Imaging mass cytometry for spatial context in tissue sections

• Single-cell Western blotting for protein quantification in individual cells

Spatial transcriptomics integration:

• Combine RHOF protein detection with spatial transcriptomics

• Correlate protein localization with local transcriptional programs

• Identify tissue microenvironments with specific RHOF activity patterns

These technologies will help address fundamental questions about RHOF biology, including its spatial organization, temporal dynamics, and context-specific functions in different cell types and disease states.

How can I develop and validate phospho-specific antibodies for RHOF to study its regulation?

Developing phospho-specific antibodies for RHOF requires a systematic approach:

Phosphorylation site identification:

• Use mass spectrometry to identify potential phosphorylation sites in RHOF

• Prioritize conserved sites across species

• Focus on sites within functional domains or regulatory regions

Peptide design considerations:

• Design phosphopeptides centered on the phosphorylation site (±5-7 amino acids)

• Include a C-terminal cysteine for conjugation if not naturally present

• Synthesize both phosphorylated and non-phosphorylated peptides

Immunization strategy:

• Use multiple rabbits (minimum 2-4) per phosphopeptide

• Follow extended immunization protocols for optimal response

• Monitor antibody titer development by ELISA

Purification workflow:

• Initial affinity purification against phosphopeptide

• Negative selection against non-phosphopeptide to remove non-phospho-specific antibodies

• Elution and concentration of phospho-specific antibodies

Rigorous validation:

• ELISA with phospho- and non-phospho-peptides

• Western blot validation using:

  • Control vs. phosphatase-treated lysates

  • Wild-type vs. phosphorylation site mutant (Ser/Thr to Ala)

  • Lysates from cells treated with kinase activators/inhibitors

• Immunoprecipitation followed by mass spectrometry to confirm target specificity

• Immunofluorescence with appropriate controls

Enhanced validation methods:

• Knockout/knockdown controls to ensure specificity

• Phosphopeptide competition assays

• Orthogonal methods for detecting phosphorylation (Phos-tag gels)

As emphasized in antibody validation literature, phospho-specific antibodies require even more stringent validation than standard antibodies, confirming both antigen specificity and phosphorylation-state specificity .