Amino Acid Length: Human ASIP is 132 aa , while mouse ASIP is 131 aa . Baboon ASIP is expected to align closely with human (~75–80% identity ).
Post-Translational Modifications: Likely includes disulfide bonds stabilizing the cystine knot structure, as observed in mouse ASIP .
Receptor Antagonism: ASIP inhibits melanocortin receptors (MC1R, MC2R, MC3R, MC4R) by blocking α-MSH/ACTH signaling .
ASIP regulates melanin synthesis and energy metabolism. In baboons, its roles may mirror those in humans and mice:
Pigmentation: Inhibits eumelanin production by antagonizing MC1R .
Adipocyte Metabolism: Modulates insulin secretion in adipose tissue .
Melanocortin Pathway: Acts as a competitive antagonist, reducing cAMP signaling in target cells .
Recombinant ASIP is used in:
Melanoma Studies: To inhibit melanin synthesis in cell models (e.g., B16F1 melanoma) .
Obesity Models: To explore metabolic regulation via MC4R antagonism .
Pharmacological Screens: For identifying ASIP-binding compounds .
Species-Specificity: No direct studies on baboon ASIP exist. Functional data are extrapolated from human and mouse models .
Detection Challenges: Low protein abundance in tissues (<12.5 ng), as observed in cattle , complicates biochemical analyses.
Receptor Binding: Potency varies across receptor subtypes (e.g., weaker at MC3R) .
UniGene: Pan.17936
Recombinant Papio anubis ASIP is a paracrine signaling molecule produced through baculovirus expression systems that functions as an antagonist of melanocortin action at melanocortin receptors. The mature ASIP protein consists of 110 amino acids (residues 23-132) with multiple cysteine residues critical for its tertiary structure .
Similar to human ASIP, Papio anubis ASIP inhibits the generation of cAMP stimulated by α-MSH or ACTH at various melanocortin receptor subtypes. Mouse agouti protein has been demonstrated to antagonize melanocortin action at several cloned rodent and human melanocortin receptors, and human ASIP exhibits inhibitory effects at five known human melanocortin receptor subtypes (hMCR 1-5) .
To effectively investigate ASIP function, researchers should:
Employ cAMP assays using cell lines expressing different melanocortin receptor subtypes
Conduct competitive binding studies with labeled melanocortin peptides
Perform comparative analyses with human and other primate ASIP proteins
Proper handling of recombinant Papio anubis ASIP is critical for maintaining its biological activity. Based on manufacturer recommendations:
Storage conditions:
Reconstitution protocol:
Stability considerations:
Researchers should verify activity after extended storage by testing antagonism of α-MSH-induced cAMP production in appropriate cell models.
Recombinant Papio anubis ASIP provides a valuable tool for comparative melanocortin receptor pharmacology studies:
Receptor subtype selectivity:
Signaling pathway analysis:
Experimental design considerations:
Use stably transfected cell lines expressing individual melanocortin receptor subtypes
Include L cells (for MC1R, MC3R, MC4R, MC5R) and adrenocortical cell lines like OS3 (for MC2R)
Employ positive controls with known melanocortin agonists
Include dose-response curves to accurately determine potency
The availability of a high-quality de novo genome assembly for Papio anubis (Panubis1.0) enables sophisticated genomic approaches to ASIP research:
Genomic analysis advantages:
Research applications:
Extract and analyze the ASIP gene locus and regulatory regions
Conduct comparative genomics with human and other primate ASIP loci
Identify conserved non-coding elements that may regulate expression
Investigate chromatin organization using Hi-C data to understand three-dimensional regulatory interactions
Methodological approaches:
Selecting appropriate cell models is crucial for valid ASIP functional studies:
Established cell lines:
Species-specific considerations:
Human cell lines expressing baboon melanocortin receptors
Baboon-derived primary cells when available
Comparative studies using both human and baboon cellular systems
Selection criteria:
Endogenous expression profile of melanocortin receptors
Transfection/transduction efficiency
Presence of appropriate downstream signaling machinery
Low background cAMP production
Validation requirements:
Confirm receptor expression by qPCR, Western blot, or immunocytochemistry
Verify receptor functionality using known agonists
Establish dose-response relationships for both agonists and ASIP
Distinguishing specific from non-specific effects requires rigorous experimental controls:
Comprehensive controls:
Analytical approaches:
Generate complete dose-response curves rather than single-point measurements
Calculate IC₅₀ values and compare across receptor subtypes
Analyze Hill coefficients for insights into binding cooperativity
Compare maximum inhibition levels to identify partial vs. full antagonism
Specificity validation methods:
Receptor mutagenesis to identify critical binding residues
Cross-competition studies with known melanocortin receptor ligands
Testing on non-melanocortin receptors to confirm specificity
Evaluation in receptor-negative parental cell lines
Comparative analysis of baboon and human ASIP reveals important evolutionary and functional insights:
Experimental design for comparative studies:
Data presentation format:
| Receptor | Parameter | Human ASIP | Papio anubis ASIP | Fold Difference |
|---|---|---|---|---|
| MC1R | IC₅₀ (nM) | [value] | [value] | [value] |
| Max inhibition (%) | [value] | [value] | [value] | |
| MC3R | IC₅₀ (nM) | [value] | [value] | [value] |
| Max inhibition (%) | [value] | [value] | [value] | |
| MC4R | IC₅₀ (nM) | [value] | [value] | [value] |
| Max inhibition (%) | [value] | [value] | [value] | |
| MC5R | IC₅₀ (nM) | [value] | [value] | [value] |
| Max inhibition (%) | [value] | [value] | [value] |
Interpretation framework:
Relate differences to sequence variations in key functional domains
Consider evolutionary conservation of critical residues
Evaluate physiological relevance of any observed differences
Assess implications for using baboon models in melanocortin research
Production of high-quality recombinant ASIP requires careful consideration of expression and purification strategies:
Expression system selection:
Purification workflow:
Quality control criteria:
Purity assessment by SDS-PAGE and silver staining
Identity confirmation by Western blot and/or mass spectrometry
Structural validation by circular dichroism
Functional validation by receptor binding and signaling assays
Production optimization strategies:
Codon optimization for expression host
Signal sequence optimization for secretion
Culture condition optimization (temperature, inducer concentration, harvest timing)
Scale-up considerations for larger quantities
Proper analysis of ASIP antagonism data requires appropriate mathematical and statistical approaches:
Dose-response curve analysis:
Plot inhibition of agonist response vs. log[ASIP concentration]
Fit data to appropriate models (competitive, non-competitive, or uncompetitive antagonism)
Calculate IC₅₀ values and confidence intervals
Determine inhibition constants (Ki) using Cheng-Prusoff equation
Schild analysis for competitive antagonists:
Generate agonist dose-response curves in presence of multiple ASIP concentrations
Plot Schild regression to determine mechanism of antagonism
Calculate pA₂ values to quantify antagonist potency
Evaluate slope for deviation from unity (competitive antagonism)
Statistical considerations:
Perform experiments in triplicate minimally
Calculate means and standard errors for key parameters
Use appropriate statistical tests to compare across conditions
Consider biological vs. technical variability in experimental design
Presentation of quantitative results:
| Analysis Parameter | Definition | Calculation Method | Interpretation |
|---|---|---|---|
| IC₅₀ | Concentration causing 50% inhibition | Non-linear regression | Measure of potency |
| Hill Coefficient | Slope of dose-response curve | Logistic equation fitting | Binding cooperativity |
| pA₂ | Negative log of antagonist concentration shifting dose-response 2-fold | Schild analysis | Affinity measure |
| Ki | Inhibition constant | Cheng-Prusoff equation | True binding affinity |
Comparative studies between Papio anubis and human ASIP provide valuable evolutionary perspectives:
Evolutionary analysis approaches:
Sequence alignment across primate species to identify conserved domains
Calculation of dN/dS ratios to detect selection signatures
Identification of species-specific variations in functional domains
Correlation of genetic differences with functional divergence
Translational research applications:
Use baboon models to study melanocortin-related disorders
Identify conserved mechanisms applicable to human health
Understand species-specific adaptations in melanocortin signaling
Develop targeted therapies based on evolutionary insights
Methodological considerations:
Investigating tissue-specific ASIP effects requires thoughtful experimental design:
Expression profiling strategy:
Analyze ASIP and melanocortin receptor expression across tissues
Use qPCR, Western blot, and immunohistochemistry for comprehensive profiling
Consider single-cell approaches to identify specific cell populations
Correlate ASIP expression with receptor distribution
Ex vivo tissue models:
Develop tissue explant systems from relevant baboon tissues
Treat with recombinant ASIP at physiologically relevant concentrations
Measure functional outcomes specific to each tissue type
Compare responses between tissues with different receptor profiles
In vivo considerations:
Design monitoring approaches for intact animals
Consider ethical and practical aspects of non-human primate research
Develop appropriate biomarkers for ASIP activity
Plan for sample collection to enable multi-omics analyses
Outcome measures by tissue type:
| Tissue Type | Melanocortin Receptors | Functional Readouts | Technical Approaches |
|---|---|---|---|
| Skin | MC1R | Melanin production | Melanin assay, histology |
| Adrenal | MC2R | Steroidogenesis | Hormone ELISA, qPCR |
| Hypothalamus | MC3R, MC4R | Energy homeostasis | Metabolic measurements |
| Adipose | MC2R, MC5R | Lipolysis | Glycerol release assay |
Researchers frequently encounter technical challenges when working with ASIP:
Protein stability issues:
Assay sensitivity limitations:
Challenge: Detecting subtle changes in cAMP levels
Solution: Use high-sensitivity detection methods (FRET-based or luminescence-based)
Optimization: Include phosphodiesterase inhibitors to prevent cAMP degradation
Cell model variability:
Challenge: Inconsistent receptor expression levels
Solution: Establish stable cell lines with verified receptor expression
Verification: Quantify receptor levels by qPCR or Western blot before experiments
Non-specific binding concerns:
Challenge: Distinguishing specific from non-specific antagonism
Solution: Include appropriate controls and competitive binding assays
Analysis: Calculate specific binding by subtracting non-specific component
Multi-omics integration provides comprehensive insights into ASIP biology:
Data integration framework:
Genomic data: Gene structure, regulatory elements, variants
Transcriptomic data: Expression patterns across tissues and conditions
Proteomic data: Protein interactions, post-translational modifications
Functional data: Receptor binding, signaling outcomes, physiological effects
Analytical approaches:
Network analysis to identify shared pathways
Machine learning for pattern recognition across data types
Pathway enrichment analysis for biological context
Cross-species comparison to identify conserved and divergent features
Visualization strategies:
Integrated genomic viewers for structural data
Heat maps for expression data across tissues
Network diagrams for protein interactions
Combined plots showing structure-function relationships
Validation requirements:
Experimental verification of key computational predictions
Orthogonal methods to confirm findings
Hypothesis testing based on integrated models
Iterative refinement of multi-omics models