ROBO2 Antibody

What is ROBO2 and what are its main functional roles in cellular processes?

ROBO2 is a transmembrane protein belonging to the immunoglobulin superfamily that functions as a receptor for SLIT2, and probably SLIT1, molecular guidance cues that regulate cellular migration and axonal navigation. The canonical human ROBO2 protein has a length of 1378 amino acids with a molecular weight of approximately 151.2 kDa .

Functionally, ROBO2 plays critical roles in:

• Axon guidance at the ventral midline of the neural tube

• Projection of axons to different regions during neuronal development

• Formation of lateral longitudinal axon pathways

• Regulation of motor axon guidance

• Cell migration in multiple developmental contexts

ROBO2 contains 5 Ig-like C2-type domains and 3 fibronectin type-III domains in its extracellular region . It localizes primarily to the cell membrane, with expression patterns that change dynamically during development . In late embryonic stages, Robo2 protein in the nervous system is largely restricted to longitudinal axons in the lateral-most region of the neuropile .

What expression patterns does ROBO2 exhibit across tissues and developmental stages?

ROBO2 shows a complex and dynamic expression pattern that varies significantly across tissue types and developmental stages, making this understanding crucial for experimental design.

In the embryonic nervous system:

• Initially shows broad expression in early neural development

• Becomes progressively restricted to specific neuronal populations

• In late stages, predominantly found in longitudinal axons in the lateral-most region of the neuropile

• Remains detectable in motor neurons (particularly ventrally-projecting RP motor neurons) through stage 17

• Shows strong expression in midline glia and midline-adjacent pioneer neurons

Non-neural embryonic expression includes:

• Anterior ectoderm during head involution

• Thoracic visceral mesoderm and chordotonal neurons

• Ectodermal stripes

• Developing heart/pericardial cells

• Tracheal branches

• Ventral longitudinal muscles

• Embryonic gonad

Post-embryonic expression includes:

• Adult posterior midgut

• Glial cells in the larval leg imaginal disc

• Adult testis

This diverse expression pattern means researchers must carefully select appropriate developmental timepoints and tissue types when designing experiments with ROBO2 antibodies.

What applications are ROBO2 antibodies validated for, and what are the optimal protocols for each?

ROBO2 antibodies have been validated for multiple research applications, each requiring specific optimization approaches:

For optimal results in neural tissue:

• Use anti-HRP as a pan-neuronal counterstain

• Consider anti-FasII for motor axons and longitudinal pathway visualization

• For developmental studies, stage-specific optimization is essential

Methodological note: When staining mouse embryonic tissue (E14), a dilution of 1/20 has been successful for detecting ROBO2 in developing olfactory bulb and nerve .

How can researchers distinguish between ROBO2 and other ROBO family members?

Distinguishing between ROBO family members (ROBO1, ROBO2, and ROBO3) requires careful experimental design due to their structural similarities but distinct functional roles:

Functional distinctions:

• ROBO1: Primarily restricts midline crossing of axons

• ROBO2: Has more dynamic roles including preventing midline crossing in some axons, promoting crossing in others, forming lateral longitudinal pathways, and regulating motor axon guidance

• ROBO3: Often acts antagonistically to ROBO1/2, promoting midline crossing

Methodological approaches:

• Genetic approaches:

  • Use of specific knockout models (such as Robo2 mutant embryos that show misguidance of dI1i axons)

  • Selective rescue experiments in knockout backgrounds

  • CRISPR-based genomic editing for specific manipulation

• Expression analysis:

  • Comparative qRT-PCR with isoform-specific primers

  • High-specificity mRNA detection methods

  • Single-cell RNA-seq to identify cell-specific expression patterns

• Protein detection strategies:

  • Western blotting with antibodies validated against all family members

  • Size discrimination (ROBO2: ~151 kDa)

  • Use of antibodies targeting non-conserved regions

  • For ROBO2, epitopes in the C-terminal region have shown good specificity

• Visualization approaches:

  • Multiplexed immunofluorescence with antibodies to different ROBO proteins

  • Co-staining with markers of specific axon populations

  • High-resolution imaging to distinguish subcellular localization patterns

When designing experiments to distinguish between ROBO family members, researchers should include appropriate controls due to the high degree of sequence homology between family members.

What is the role of ROBO2 in cancer and disease models?

ROBO2 has emerging roles in cancer biology and disease pathology:

Cancer implications:

• Acts as a stroma suppressor gene in pancreatic tissue

• Loss of epithelial ROBO2 expression is observed in pancreatitis and pancreatic ductal adenocarcinoma (PDAC) mouse models

• ROBO2 expression is generally low in PDAC patients

• Patients with ROBO2low;ROBO1high expression pattern show poorest survival outcomes

• ROBO2 functions non-autonomously by restraining myofibroblast activation and T-cell infiltration

Disease associations:

• Defects in ROBO2 are the cause of vesicoureteral reflux type 2 (VUR2)

• VUR is characterized by retrograde flow of urine from the bladder into the ureter

• Associated with reflux nephropathy, the cause of 15% of end-stage renal disease in children and young adults

• Chromosomal aberrations involving ROBO2 can cause multiple congenital abnormalities

Experimental approaches:

• Cancer models:

  • Conditional knockout models (e.g., Pdx1Cre;Robo2F/F for pancreatic studies)

  • Analysis of myofibroblast activation in ROBO2-deficient systems

  • Examination of TGF-β and Wnt pathway activation

  • Response to pathway inhibitors (e.g., galunisertib for TGF-β inhibition)

• Disease models:

  • Examination of ureter development in ROBO2-deficient models

  • Analysis of ROBO2 mutations in patient cohorts with VUR

  • Functional studies of ROBO2 variants found in clinical samples

These findings suggest ROBO2 status could guide therapy with TGF-β inhibitors or other stroma/immune modulating agents in cancer treatment .

What are the challenges in detecting ROBO2 in different experimental systems?

Detecting ROBO2 presents several technical challenges that researchers should anticipate:

Protein extraction challenges:

• As a transmembrane protein, ROBO2 can be difficult to solubilize

• Specialized membrane protein extraction buffers are recommended

• High molecular weight (151.2 kDa) requires extended run times and efficient transfer conditions for Western blotting

Expression variability:

• ROBO2 expression is highly dynamic during development

• Up to 3 different isoforms have been reported for this protein

• Expression can be widely distributed across many tissue types

• Precise developmental staging is critical when comparing expression patterns

Detection specificity:

• Potential cross-reactivity with other ROBO family members

• Include positive controls with overexpressed ROBO2

• Use ROBO2 knockout/knockdown samples as negative controls

• Verify results with antibodies targeting different epitopes

Sample preparation considerations:

• For immunohistochemistry, heat-mediated antigen retrieval with citrate buffer pH 6 is recommended

• For neural tissue, co-staining with neural markers (HRP, FasII) enhances interpretation

• Fresh frozen tissue may preserve epitopes better than paraffin processing in some cases

Visualization challenges:

• Subcellular localization primarily in membrane requires appropriate permeabilization

• In neural tissue, complex 3D architecture can complicate interpretation

• Cellular heterogeneity in complex tissues requires cell-type specific approaches

• Multiple labeling strategies may be needed to identify specific ROBO2-expressing neuronal populations

Addressing these challenges through careful experimental design and appropriate controls will improve the reliability and interpretability of ROBO2 detection.

How can researchers effectively study ROBO2-SLIT interactions?

Studying ROBO2-SLIT interactions requires specialized approaches due to the nature of these receptor-ligand interactions:

Key interaction characteristics:

• ROBO2 is a receptor for SLIT2, and probably SLIT1

• These interactions guide cellular migration and axonal navigation

• The interactions are critical during neural tube development and axonal projection formation

Recommended methodological approaches:

• Binding studies:

  • Solid-phase binding assays using purified proteins

  • Surface plasmon resonance to determine binding kinetics

  • Co-immunoprecipitation to detect physical interactions

• Functional response assays:

  • Growth cone collapse assays with purified SLIT proteins

  • Cell migration assays in response to SLIT gradients

  • Neurite outgrowth assays with SLIT-expressing cell overlays

• In vivo interaction studies:

  • Expression of fluorescently tagged ROBO2 and SLIT proteins

  • Analysis of axon guidance in models with SLIT or ROBO2 manipulation

  • Genetic interaction studies combining ROBO2 and SLIT mutations

• Structural approaches:

  • Analysis of ROBO2 domains involved in SLIT binding

  • Computational modeling of interaction interfaces

  • Structure-based design of interaction modulators

Critical controls:

• Species matching: Ensure ROBO2 and SLIT proteins are from the same species or confirmed to interact across species

• Isoform specificity: Account for potential differential interactions between specific ROBO2 and SLIT isoforms

• Concentration ranges: Test physiologically relevant concentration ranges

• Positive controls: Include well-characterized receptor-ligand pairs

• Negative controls: Use unrelated proteins with similar structural features

These approaches will enable researchers to characterize ROBO2-SLIT interactions and their functional consequences in various biological contexts.

What approaches are recommended for studying ROBO2 function in neural development?

Studying ROBO2 function in neural development requires specialized approaches:

In vivo approaches:

• Conditional knockout models using tissue-specific promoters

• In utero electroporation for spatiotemporal manipulation

• Open-book preparations of neural tissue for visualization

• Analysis of dI1i axon guidance which specifically depends on ROBO2 function

Visualization strategies:

• Use GAL4 enhancer fragments that drive expression in specific ROBO2-expressing cell types

• Implement sparse labeling techniques to visualize individual axons

• Employ fluorescent reporters under control of ROBO2 regulatory elements

• Examine lateral longitudinal neurons where ROBO2 is particularly important

Functional assessment:

• Quantification of axon navigation decision points

• Analysis of specific guidance events such as midline crossing

• Examination of lateral longitudinal pathway formation

• Comparison between different neuronal subtypes (eg., dI1c versus dI1i neurons)

Molecular approaches:

• Identification of ROBO2 enhancer elements that control expression in specific cell types

• Analysis of ROBO2's dynamic expression pattern through development

• Comparison with co-expressed guidance molecules

• Investigation of how ROBO2 differentially affects ipsilateral versus contralateral neurons

Advanced techniques:

• Use of robo2 GAL4/UAS-TMG systems to visualize ROBO2-expressing neurons

• Anti-HA staining of modified robo2 loci including an N-terminal 4xHA tag

• Triple-labeling with anti-HRP (all axons) and anti-FasII (specific pathways)

By implementing these approaches, researchers can effectively study the complex roles of ROBO2 in neural development, particularly its functions in axon guidance and cellular migration.

How should ROBO2 antibodies be validated for experimental use?

Rigorous validation of ROBO2 antibodies is essential for reliable experimental results:

Validation strategies:

• Genetic validation:

  • Testing in ROBO2 knockout/knockdown tissues

  • Comparison between wild-type and ROBO2-deficient samples

  • Rescue experiments with ROBO2 expression constructs

• Expression pattern confirmation:

  • Comparison with established ROBO2 expression patterns

  • Verification against RNA expression data

  • Correlation with known developmental and tissue-specific expression

• Specificity testing:

  • Western blot should show a band at the expected molecular weight (~151.2 kDa)

  • Testing for cross-reactivity with other ROBO family members

  • Pre-absorption with immunizing peptide should eliminate specific signal

  • Comparison of results using antibodies targeting different ROBO2 epitopes

• Application-specific validation:

  • For IHC: Known positive tissues (developing olfactory bulb, cerebral cortex neuronal processes, placenta)

  • For IF: Cellular localization primarily at the membrane

  • For WB: Clear band at expected molecular weight with minimal background

  • For IP: Confirmation of pulled-down protein by mass spectrometry

• Species cross-reactivity:

  • Testing across species when using in non-human models

  • Verification in human, mouse, and rat tissues when claimed

  • Confirmation of epitope conservation across species

Recommended positive controls:

• Developing neural tissue (particularly olfactory bulb and nerve in E14 mouse embryos)

• SH-SY5Y neuroblastoma cells for IF

• Human cerebral cortex for neuronal processes

• Placental trophoblastic cells

Recommended negative controls:

• Human kidney tissue typically shows negative staining

• Secondary antibody-only controls

• Isotype controls for monoclonal antibodies

• Non-transfected cells when testing overexpression systems

Thorough validation ensures antibody specificity and reliability across experimental applications.

What are the best approaches for quantifying ROBO2 expression in complex tissues?

Quantifying ROBO2 expression in complex tissues requires careful methodological consideration:

Recommended approaches:

• Image-based quantification:

  • Use consistent acquisition parameters across samples

  • Implement automated image analysis with uniform thresholding

  • Account for cellular heterogeneity through cell-type specific markers

  • Consider Z-stack acquisition for 3D tissues with complex architecture

• Biochemical quantification:

  • Subcellular fractionation to separate membrane-bound ROBO2

  • Normalization to appropriate housekeeping proteins

  • Western blot densitometry with standard curves

  • ELISA-based approaches for higher sensitivity and throughput

• Transcript quantification:

  • qRT-PCR with isoform-specific primers

  • RNA-seq for comprehensive transcriptome analysis

  • In situ hybridization for spatial information

  • Single-cell approaches for heterogeneous tissues

Challenges and solutions:

• Heterogeneous expression:

  • Use laser capture microdissection for isolating specific regions

  • Implement single-cell approaches when feasible

  • Employ multiplexed immunofluorescence to identify specific cell populations

• Dynamic expression during development:

  • Create precise developmental series with standardized staging

  • Document exact developmental timepoints

  • Include known stage-specific markers as internal references

• Membrane localization challenges:

  • Use membrane markers for co-localization and normalization

  • Implement membrane vs. cytoplasmic fractionation protocols

  • Consider surface biotinylation approaches for surface-specific quantification

• Low abundance in certain contexts:

  • Implement signal amplification methods

  • Consider enrichment strategies prior to analysis

  • Use more sensitive detection methods for challenging samples

By addressing these methodological considerations, researchers can achieve more reliable quantification of ROBO2 expression across diverse experimental contexts.

Roundabout Guidance Receptor 2: ROBO2 Antibody Research Considerations

This comprehensive FAQ guide provides methodological insights for researchers working with ROBO2 antibodies across diverse experimental contexts. Understanding the complex biology of ROBO2 and selecting appropriate detection strategies is essential for generating reliable and interpretable data in developmental, cancer, and disease-focused research programs.