Artn Antibody

What is Artemin (ARTN) and why is it important in scientific research?

Artemin (ARTN), also known as enovin or neublastin, is a neurotrophic factor in the glial cell line-derived neurotrophic factor family of ligands within the TGF-beta superfamily. It is encoded by the ARTN gene in humans and plays significant roles in both peripheral and central nervous systems .

ARTN is particularly important in research because:

• It supports the survival of peripheral neuron populations and certain dopaminergic CNS neurons

• It functions as a chemoattractant for sympathetic neuron axons innervating the developing cardiovascular system

• It promotes sensory neuron survival and contributes to peripheral nervous system development

• It has been implicated in neuropathic pain reversal and nerve damage repair

• It has been linked to cancer progression in certain contexts, including mammary and endometrial carcinomas

The multifaceted roles of ARTN make antibodies against this protein valuable tools for studying nervous system development, pain modulation, cancer biology, and neurodegenerative conditions.

What applications are ARTN antibodies commonly used for?

Based on the available research data, ARTN antibodies are primarily used in the following experimental applications:

• Western blotting - For detecting ARTN protein expression in cell lysates and tissue samples

• Immunoprecipitation - To isolate ARTN protein complexes and study protein-protein interactions

• ELISA (Enzyme-Linked Immunosorbent Assay) - For quantitative measurement of ARTN levels

• Immunohistochemistry - To visualize ARTN distribution in tissue sections

ARTN antibodies have been instrumental in studies examining:

• Estrogen regulation of ARTN in mammary carcinoma and antiestrogen resistance mechanisms

• ARTN's role in promoting oncogenicity and invasiveness in endometrial carcinoma cells

• ARTN-mediated angiogenesis through TWIST1-VEGF-A signaling pathways in ER-negative mammary carcinoma

What are the key considerations for storing and handling ARTN antibodies?

Proper storage and handling of ARTN antibodies is crucial for maintaining their functionality and specificity. Based on manufacturer recommendations:

• Use a manual defrost freezer and avoid repeated freeze-thaw cycles to prevent antibody degradation

• Store unopened antibodies at -20°C to -70°C for up to 12 months from the date of receipt

• After reconstitution, store at 2-8°C under sterile conditions for up to 1 month for immediate use

• For long-term storage after reconstitution, aliquot and store at -20°C to -70°C for up to 6 months under sterile conditions

The reconstitution method also matters significantly. Always follow the manufacturer's specific instructions, as improper reconstitution can lead to loss of antibody activity or increased background in assays.

How can epitope selection impact the efficacy of ARTN antibodies in targeting specific protein conformations?

Epitope selection is critical when studying ARTN, particularly due to its structure and functional domains. ARTN, like other GDNF family members, is synthesized as a preproprotein containing a signal sequence, a proregion, and a mature segment .

When targeting ARTN with antibodies, researchers should consider:

• The mature form of ARTN (aa 108-220 in humans) exists as a disulfide-linked homodimer with three intrachain disulfide bonds and a characteristic cysteine-knot motif . Antibodies targeting different epitopes within this region may have varying abilities to recognize the active protein.

• Alternative splicing creates different signal sequences (22, 30, or 39 amino acids) , which may affect antibody recognition depending on the target epitope.

• Post-translational modifications, particularly glycosylation of the secreted 28 kDa form , can mask epitopes or alter antibody binding.

For optimal results, researchers should select antibodies targeting epitopes that:

• Are accessible in the folded protein

• Don't interfere with functional domains if studying protein activity

• Are conserved across species if cross-reactivity is desired (human ARTN is 89% and 88% identical to rat and mouse ARTN in the mature region, respectively)

What methodological approaches should be considered when using ARTN antibodies to study its role in cancer progression?

When investigating ARTN's role in cancer progression, several methodological considerations are essential:

• Selection of appropriate cellular models:

  • Previous studies have successfully used ARTN antibodies to examine its role in mammary carcinoma (both ER-positive and ER-negative)

  • Endometrial carcinoma cells have also been studied in relation to ARTN-mediated oncogenicity and invasiveness

• Complementary techniques:

  • Combine immunoblotting with functional assays to correlate ARTN expression with phenotypic changes

  • Use RNA interference alongside antibody neutralization studies to distinguish between correlation and causation

  • Implement immunoprecipitation to identify binding partners in cancer-specific signaling networks

• Pathway analysis:

  • ARTN has been linked to TWIST1-VEGF-A signaling in promoting angiogenesis

  • Consider examining both upstream regulators (such as estrogen) and downstream effectors when designing experiments

• Controls and validation:

  • Use multiple antibodies targeting different epitopes to validate findings

  • Include appropriate positive controls (cells known to express ARTN, such as Schwann cells or embryonic vascular smooth muscle cells)

  • Verify antibody specificity through knockout/knockdown validation

What are the key considerations when designing experiments to evaluate ARTN's role in neurodegeneration using antibodies?

When investigating ARTN's neuroprotective functions in the context of neurodegeneration:

• Model selection:

  • In vitro neuronal cultures: Primary sympathetic or sensory neurons are appropriate models given ARTN's known effects on these populations

  • Ex vivo preparations: Ganglion explants can be useful for studying axonal growth

  • In vivo models: Consider nerve injury models where ARTN has been shown to reverse neuropathic pain and morphological changes

• Experimental design:

  • Functional blocking experiments: Use antibodies that neutralize ARTN to determine its necessity in neuronal survival

  • Temporal considerations: ARTN may have different effects depending on developmental stage or time post-injury

  • Dose-response relationships: Establish appropriate antibody concentrations through titration experiments

• Readouts:

  • Morphological measures: Axon growth, dendritic arborization

  • Survival assays: Apoptotic markers, cell viability

  • Functional measures: Electrophysiological recordings, behavioral assessments for in vivo studies

• Mechanistic investigations:

  • Co-immunoprecipitation to identify ARTN interactions with GFR alpha-3/RET receptor complex

  • Phosphorylation status of downstream signaling components

  • Transcriptional changes following ARTN application or neutralization

How can researchers validate the specificity of ARTN antibodies to avoid cross-reactivity with other GDNF family members?

Validating antibody specificity is crucial when studying ARTN due to structural similarities with other GDNF family members. A comprehensive validation approach should include:

• Sequence-based analysis:

  • Compare the immunogen sequence used to generate the antibody with other GDNF family members

  • Antibodies raised against synthetic peptides corresponding to specific ARTN regions (e.g., aa 101-150) may offer higher specificity than those targeting whole protein

• Experimental validation:

  • Western blot analysis using recombinant ARTN alongside other GDNF family proteins

  • ELISA competition assays with related proteins

  • Testing on samples with known expression profiles (positive and negative controls)

  • Using knockout/knockdown models to confirm signal specificity

• Additional controls:

  • Pre-absorption of antibody with immunizing peptide should eliminate specific signal

  • Use of multiple antibodies targeting different epitopes should yield consistent results

  • Secondary antibody-only controls to rule out non-specific binding

A systematic validation approach increases confidence in experimental findings and helps avoid misinterpretation of results due to antibody cross-reactivity.

What technical challenges might researchers encounter when using ARTN antibodies in different experimental contexts?

Researchers may encounter several technical challenges when working with ARTN antibodies:

• Western blotting challenges:

  • Detection of dimeric vs. monomeric forms: ARTN exists as a disulfide-linked homodimer , requiring consideration of reducing vs. non-reducing conditions

  • Post-translational modifications: Glycosylation of secreted ARTN may affect migration patterns and antibody recognition

  • Protein extraction methods: Ensuring complete extraction of membrane-associated or secreted ARTN

• Immunohistochemistry/immunofluorescence considerations:

  • Fixation sensitivity: Some epitopes may be masked by certain fixatives

  • Antigen retrieval requirements: Optimization may be needed for formalin-fixed tissues

  • Background issues: Non-specific binding can be problematic, requiring careful blocking optimization

• Species cross-reactivity limitations:

  • While human ARTN shares high sequence homology with rodent orthologs (88-89% in mature regions) , antibody performance may vary across species

  • Validation is essential when switching between human and animal models

• Functional assays:

  • Neutralizing capacity varies between antibodies depending on epitope location

  • Concentration requirements may differ substantially between detection and functional applications

What is the optimal approach for designing antibody-based experiments to differentiate between ARTN's membrane-bound and secreted forms?

ARTN exists in both membrane-associated and secreted forms, and distinguishing between these populations requires careful experimental design:

• Subcellular fractionation approach:

  • Separate membrane fractions from culture supernatants or tissue extracts

  • Use differential centrifugation to isolate membrane-bound proteins

  • Compare ARTN immunoreactivity between fractions using validated antibodies

  • Include appropriate markers for each fraction (e.g., Na+/K+ ATPase for membrane fractions)

• Selective immunoprecipitation:

  • Use surface biotinylation techniques to label only membrane-exposed proteins

  • Immunoprecipitate with ARTN antibodies

  • Compare biotinylated vs. non-biotinylated ARTN population

• Live-cell imaging:

  • Use non-permeabilizing conditions to detect only cell-surface ARTN

  • Compare with permeabilized conditions to visualize intracellular pools

  • Consider epitope accessibility when selecting antibodies

• Temporal analysis:

  • Pulse-chase experiments to track newly synthesized ARTN from intracellular to secreted pools

  • Time-course analysis of culture media to quantify secretion rates

What strategies can resolve inconsistent results when using ARTN antibodies in Western blot applications?

Inconsistent Western blot results with ARTN antibodies can be addressed through systematic troubleshooting:

• Sample preparation optimization:

  • Ensure complete protein denaturation (appropriate buffer and heating)

  • Consider reducing vs. non-reducing conditions based on the target epitope

  • Use freshly prepared samples and avoid repeated freeze-thaw cycles

  • Include protease inhibitors to prevent degradation

• Antibody-specific adjustments:

  • Titrate antibody concentration to determine optimal working dilution

  • Adjust incubation time and temperature

  • Try different blocking reagents to reduce background

  • Consider using alternative antibodies targeting different epitopes

• Detection system considerations:

  • Compare chemiluminescence vs. fluorescence-based detection

  • Optimize exposure times to prevent oversaturation

  • Ensure secondary antibody compatibility

• Positive and negative controls:

  • Include recombinant ARTN protein as a positive control

  • Use cell lines with known ARTN expression profiles

  • Consider using ARTN knockdown samples as negative controls

How can researchers address structural accuracy concerns when using antibodies for ARTN protein interaction studies?

When studying ARTN protein interactions, structural accuracy concerns should be addressed:

• Structure preservation strategies:

  • Use mild lysis conditions that maintain protein-protein interactions

  • Consider crosslinking approaches to stabilize transient interactions

  • Select antibodies validated for immunoprecipitation applications

• Epitope accessibility considerations:

  • Choose antibodies targeting regions unlikely to be involved in protein-protein interactions

  • Consider competing binding partners when selecting epitopes

  • Test multiple antibodies to find those that don't disrupt critical interactions

• Validation approaches:

  • Confirm findings with complementary techniques (e.g., proximity ligation assay)

  • Use reciprocal co-immunoprecipitation to verify interactions

  • Implement mass spectrometry to identify interaction partners in an unbiased manner

• Addressing modeling artifacts:

  • Be aware that computational models may contain structural inaccuracies (like cis-amide bonds, D-amino acids, or clashes)

  • Use validation tools to inspect protein structure models

  • Consider the high variability of certain protein regions that cannot be captured in static models

How are rational design approaches changing the landscape of ARTN-targeted antibody development?

Recent advances in rational antibody design are transforming ARTN research:

• Epitope-specific targeting strategies:

  • Complementary peptide identification methods allow for the generation of antibodies targeting specific epitopes within disordered proteins

  • Grafting of complementary peptides onto antibody CDR loops enables precise epitope targeting

  • These approaches allow for the development of antibodies against weakly immunogenic epitopes that may be challenging with traditional methods

• Structure-based design considerations:

  • Selection of stable antibody scaffolds tolerant to CDR loop modifications

  • Use of human heavy chain variable (VH) domains that remain stable without light chain partners

  • Focus on scaffolds that maintain proper folding despite insertions in CDR3 regions

• Applications in neurodegenerative research:

  • Rationally designed antibodies have successfully targeted disordered proteins involved in neurodegenerative diseases

  • Some designed antibodies can inhibit protein aggregation at substoichiometric concentrations

  • These approaches enable targeting of specific epitopes within disordered regions of proteins like ARTN

This rational design methodology represents a significant advance over traditional antibody production techniques, offering greater specificity, reduced time and cost, and the ability to target challenging epitopes.

What considerations should researchers make when evaluating AI-predicted antibody structures for ARTN-binding studies?

With the advancement of AI-based protein structure prediction tools, researchers should be aware of both the benefits and limitations when applying these to ARTN antibody studies:

• Common structural inaccuracies:

  • AI-predicted models may contain non-natural features such as cis-amide bonds, D-amino acids, and severe clashes

  • CDR loops, particularly CDR-H3, show substantial structural variability that may not be accurately captured by a single static structure (RMSD values >2 Å)

  • These inaccuracies can significantly affect biophysical property predictions and docking simulations

• Model validation approaches:

  • Use specialized tools like "TopModel" to inspect protein structure models and identify structural flaws

  • Perform additional validation steps beyond the basic AI prediction

  • Consider ensemble modeling approaches to capture the dynamic nature of antibody CDR loops

• Tool selection considerations:

  • Different antibody modeling tools have varying strengths and weaknesses

  • Tools like DeepAb and Immunebuilder avoid introducing D-amino acids

  • Immunebuilder performs physical plausibility checks for steric clashes, cis-amide bonds, and bonds with nonphysical lengths

• Impact on ARTN-binding predictions:

  • Structural inaccuracies can distort metrics that rely on accurate CDR-H3 structures

  • This affects antibody-antigen docking predictions since CDR-H3 is often central to the binding interface

  • Structure-based hydrophobicity calculations may be misleading if based on models with artifacts