CHN1 Antibody

What is CHN1 and what cellular functions does it regulate?

CHN1 (Chimerin 1) functions as a GTPase-activating protein for p21-rac and serves as a phorbol ester receptor. It plays crucial roles in the assembly of neuronal locomotor circuits, acting as a direct effector of EPHA4 in axon guidance . CHN1 exists in multiple isoforms including α1-chimaerin and α2-chimaerin, with α2-chimaerin containing an N-terminal SH2 domain not present in α1-chimaerin . The protein regulates Rac activity through its RacGAP domain and interacts with membrane-associated phorbol ester signaling lipids via its C1 domain .

What are the common synonyms for CHN1 in scientific literature?

When searching scientific literature, it's important to include all potential synonyms: ARHGAP2, CHN, N-chimaerin, A-chimaerin, Alpha-chimerin, N-chimerin, Rho GTPase-activating protein 2, RHOGAP2, and NC . This comprehensive approach ensures retrieval of all relevant publications, as different research groups may use varying nomenclature.

How do I select the appropriate CHN1 antibody for my research application?

Selection should be based on:

• Application compatibility: Verify antibody validation for your specific application (WB, IHC, ELISA, etc.)

• Species reactivity: Confirm reactivity with your experimental species (human, mouse, rat, etc.)

• Clonality considerations: Polyclonal antibodies offer broader epitope recognition, while monoclonal antibodies provide greater specificity and reproducibility

• Validation data: Review published literature citing the antibody and manufacturer validation images

Note: Always optimize antibody dilutions for your specific experimental conditions .

What are the optimal conditions for Western blot detection of CHN1?

For Western blot detection of CHN1:

• Expected molecular weight: CHN1 appears at approximately 53 kDa

• Antibody dilution: Use 1:500-1:2000 for primary antibody

• Sample preparation: Human cell lines successfully used include HEK-293T, MCF7, Jurkat, HeLa, and SH-SY5Y

• Loading control selection: Standard loading controls are appropriate

• Detection system: Both ECL and fluorescence-based secondary detection systems work effectively

For challenging samples, consider:

• Increasing protein loading to 20-30 μg

• Using RIPA buffer supplemented with protease inhibitors

• Optimizing transfer conditions for higher molecular weight proteins

• Employing gradient gels (4-15%) for better resolution

How can I optimize immunohistochemical (IHC) detection of CHN1 in tissue samples?

For optimal IHC detection:

• Antigen retrieval: Use TE buffer pH 9.0 (preferred) or citrate buffer pH 6.0

• Antibody dilution: Start with 1:50-1:500 dilution and optimize

• Positive control tissues: Human gliomas tissue and mouse brain tissue show reliable positivity

• Blocking conditions: 5% normal serum in PBS for 1 hour at room temperature

• Incubation time: Overnight at 4°C for primary antibody provides optimal signal-to-noise ratio

• Signal amplification: Consider using polymer-based detection systems for enhanced sensitivity in low-expression samples

What troubleshooting approaches are recommended for inconsistent CHN1 antibody results?

When facing inconsistent results:

• Antibody validation: Verify antibody specificity using positive controls (HEK-293T, MCF7 cells) and negative controls

• Sample preparation: Ensure complete protein denaturation and appropriate sample buffer composition

• Epitope accessibility: Different fixation protocols may affect epitope exposure; test multiple fixation methods

• Cross-reactivity: Confirm antibody specificity through immunoprecipitation followed by mass spectrometry

• Isoform specificity: Determine if your antibody recognizes specific CHN1 isoforms (α1 vs α2)

• Storage conditions: Aliquot antibodies to avoid freeze-thaw cycles and store according to manufacturer recommendations (typically -20°C in glycerol)

How does CHN1 expression correlate with clinical outcomes in cancer research?

Recent studies have established significant correlations between CHN1 expression and cancer outcomes:

• Diffuse Large B-Cell Lymphoma (DLBCL):

  • High CHN1 expression is associated with favorable outcomes in DLBCL patients

  • Particularly significant in germinal center B-cell-like subtype, stage III-IV, or IPI score >2

  • Multivariate Cox regression analysis confirmed CHN1 as an independent prognostic factor

• Gastric Cancer (GC):

  • Upregulated CHN1 transcription and protein expression in GC patients

  • High expression linked to poor survival

  • Associated with immune infiltrates and multiple cancer-related pathways

  • Potential involvement in DNA methylation processes

• Cervical Cancer:

  • CHN1 expression linked to aggressive behavior of cervical cancer cells

  • Correlation with lymph node metastasis

  • Regulated by miR-205

These findings suggest that CHN1 could serve as a clinically relevant biomarker with potential therapeutic implications in multiple cancer types .

What is known about the role of CHN1 mutations in neurological disorders?

CHN1 mutations have been implicated in neurological disorders, particularly:

• Duane's Retraction Syndrome (DRS): A congenital eye movement disorder characterized by aberrant development of axon projections to extraocular muscles

• Mechanism: Gain-of-function heterozygous missense mutations in CHN1 increase α2-chimaerin RacGAP activity

• Molecular consequences:

  • Enhanced α2-chimaerin membrane translocation

  • Increased ability to form complexes with itself

  • Hyperactivation resulting in aberrant cranial motor neuron development

Seven specific nucleotide substitutions have been identified (L20F, I126M, Y143H, A223V, G228S, P252Q, E313K), all affecting highly conserved amino acids. The mutations alter the development of ocular motor axons, as demonstrated through in ovo expression studies .

How can I assess CHN1's interaction with the RacGTP pathway in my experimental system?

To investigate CHN1's interaction with RacGTP pathways:

• Co-immunoprecipitation assays:

  • Use anti-CHN1 antibodies for pulldown experiments

  • Analyze associated proteins by western blot or mass spectrometry

  • Include PMA (phorbol 12-myristate 13-acetate) treatment to enhance membrane association

• Rac activation assays:

  • Utilize PAK-PBD pulldown assays to measure active Rac-GTP levels

  • Compare Rac activity in CHN1-overexpressing versus control cells

  • Assess effects of PMA or other stimuli on Rac activation

• Membrane translocation studies:

  • Use fluorescently tagged CHN1 constructs to monitor subcellular localization

  • Quantify translocation following stimulation with PMA or physiological agonists

  • Compare wild-type versus mutant CHN1 proteins

• Functional downstream assays:

  • Analyze actin cytoskeleton remodeling using phalloidin staining

  • Assess changes in cell migration, adhesion, or neurite outgrowth

  • Implement siRNA-mediated knockdown to confirm specificity

How do CHN1 isoforms differ in function and detection requirements?

CHN1 exists in two main isoforms with distinct functional properties and detection considerations:

Research shows that α1- and α2-chimaerin have different subcellular localization patterns and responses to stimuli. When designing experiments, consider:

• Using isoform-specific antibodies when possible

• Confirming antibody specificity for your isoform of interest

• Noting that α1-chimaerin and α2-chimaerin do not co-immunoprecipitate with each other

What are the best approaches for studying CHN1-mediated signaling pathways in neuronal systems?

For neuronal CHN1 studies:

• Model systems selection:

  • Primary neurons: Most physiologically relevant

  • Neuroblastoma cell lines: SH-SY5Y cells show reliable CHN1 expression

  • In vivo models: Chicken embryos for in ovo electroporation studies

• Pathway analysis techniques:

  • Phosphoproteomics to identify downstream signaling events

  • Live-cell imaging with fluorescent biosensors for Rac activity

  • Axon guidance assays to assess functional outcomes

• Specialized neuronal assays:

  • Growth cone collapse assays following Ephrin stimulation

  • Time-lapse microscopy of neurite extension/retraction

  • Axon pathfinding analysis in 3D culture systems

  • Quantitative assessment of neuronal morphology and branching patterns

• Gene manipulation approaches:

  • CRISPR/Cas9 editing to introduce specific CHN1 mutations

  • Conditional knockout models to study temporal requirements

  • Domain-specific mutations to dissect functional contributions

How can I establish reliable positive and negative controls for CHN1 immunodetection?

Establishing proper controls is critical for reliable CHN1 detection:

Positive controls:

• Cell lines: HEK-293T, MCF7, Jurkat, HeLa, and SH-SY5Y cells have confirmed CHN1 expression

• Tissue samples: Human gliomas tissue and mouse brain tissue

• Overexpression systems: Transfection with CHN1 expression constructs

• Recombinant proteins: Purified CHN1 protein at known concentrations

Negative controls:

• Antibody validation: Use pre-immune serum or isotype control antibodies

• Antigen competition: Pre-incubate antibody with excess immunizing peptide

• Genetic approaches: CHN1 knockdown/knockout samples

• Tissue-specific negativity: Identify tissues with minimal CHN1 expression

Additional validation approaches:

• Multiple antibody verification: Use antibodies targeting different epitopes

• Mass spectrometry confirmation of immunoprecipitated proteins

• Cross-species reactivity testing to confirm evolutionary conservation

• Isoform-specific detection to distinguish between α1 and α2 chimaerin

How is CHN1 involved in immune cell function and potential immunotherapeutic applications?

Emerging research indicates that CHN1 plays significant roles in immune function:

• Immune cell infiltration:

  • CHN1 expression correlates with immune infiltrates in gastric cancer

  • CIBERSORT algorithm analysis shows association with specific immune cell populations

• T-cell related functions:

  • Gene set enrichment analysis (GSEA) has linked CHN1 to T cell immune infiltration

  • May influence T-cell receptor signaling and downstream functions

• Immunotherapeutic implications:

  • CHN1 expression correlates with immunotherapeutic response in cancer

  • May serve as a biomarker for predicting immunotherapy efficacy

  • Potential target for enhancing immunotherapeutic approaches

Future research directions include:

• Investigating the role of CHN1 in regulating immune synapse formation

• Exploring CHN1 as a predictive biomarker for checkpoint inhibitor response

• Developing CHN1-targeted approaches to modulate immune cell function

What novel techniques are advancing our understanding of CHN1 regulation and function?

Cutting-edge techniques being applied to CHN1 research include:

• Single-cell analysis:

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

  • Mass cytometry (CyTOF) for protein-level analysis in heterogeneous samples

• Advanced imaging approaches:

  • Super-resolution microscopy to visualize CHN1 subcellular localization

  • FRET/FLIM imaging to study protein-protein interactions in live cells

  • Optogenetic control of CHN1 activity for spatiotemporal regulation

• Structural biology advances:

  • Cryo-EM studies of CHN1 complexes with interacting partners

  • Hydrogen-deuterium exchange mass spectrometry for conformational analysis

  • Molecular dynamics simulations to predict mutation effects

• Functional genomics:

  • CRISPR screens to identify synthetic lethal interactions

  • Epigenetic profiling to understand CHN1 regulation

  • Long-read sequencing to characterize complex genetic alterations

These approaches will help elucidate the complex regulatory mechanisms and functional roles of CHN1 in both normal physiology and disease states.

How do methylation patterns affect CHN1 expression in various pathological conditions?

Research has begun to uncover the role of methylation in regulating CHN1 expression:

• Cancer-related methylation:

  • Studies in gastric cancer indicate that CHN1's pro-carcinogenic role may involve DNA methylation

  • Altered methylation patterns may contribute to aberrant CHN1 expression

• Methylation analysis approaches:

  • Bisulfite sequencing to map CpG methylation in CHN1 promoter regions

  • Methylation-specific PCR for targeted analysis of key regulatory elements

  • Genome-wide methylation arrays to identify differential methylation patterns

  • CRISPR-mediated epigenetic editing to study the functional consequences of specific methylation sites

• Clinical correlations:

  • Methylation status of CHN1 may serve as a biomarker for disease progression

  • Integration of methylation data with expression profiles provides insights into regulatory mechanisms

  • Therapeutic approaches targeting methylation may modulate CHN1 expression

Further investigation of methylation patterns and their relationship to CHN1 expression across different pathological conditions represents an important direction for future research .