CHGA Human, His

What is Chromogranin A and what are its primary biological functions?

Chromogranin A (CHGA), also identified as pituitary secretory protein I (SP-I), belongs to the granin family of regulated secretory proteins. CHGA demonstrates several defining characteristics of the granin family, including an acidic isoelectric point, calcium ion binding capacity, aggregation properties, and multiple dibasic cleavage sites. The mature human CHGA protein consists of 439 amino acids containing 10 dibasic proteolytic cleavage sites that can generate several smaller peptides, each with unique functional properties .

The primary biological functions of CHGA include:

• Catalyzing the formation of catecholamine storage vesicles

• Serving as a precursor to catestatin, which inhibits catecholamine secretion

• Regulating sympathochromaffin activity and cardiovascular function

• Contributing to blood pressure regulation through catecholamine modulation

Research has shown that diminished expression of catestatin, a peptide fragment derived from CHGA, is associated with hypertension, demonstrating the protein's physiological importance in cardiovascular regulation .

How is recombinant Human CHGA His-tag protein structurally characterized?

Recombinant Human CHGA His-tag protein is characterized by specific structural elements that facilitate its use in research applications. The commercially available recombinant form typically contains:

• Amino acid sequence spanning Leu19-Gly457 of the mature human protein

• A C-terminal 6-Histidine tag for purification and detection purposes

• Molecular weight appearing at 60-80 kDa in SDS-PAGE analysis under both reducing and non-reducing conditions

• Proper folding that maintains functional domains essential for biological activity

The His-tag modification enables efficient purification through metal affinity chromatography while preserving the protein's native functional properties. This recombinant form provides researchers with a well-defined, consistent reagent for investigating CHGA's biological roles and interactions with other molecules.

What are the optimal storage and reconstitution conditions for recombinant Human CHGA His-tag protein?

Proper handling of recombinant Human CHGA His-tag protein is essential for maintaining its stability and biological activity in research applications. Based on manufacturer specifications, the following protocols should be observed:

Reconstitution Protocol:

• The lyophilized protein should be reconstituted at a concentration of 200 μg/mL in PBS

• Ensure complete solubilization by gentle mixing rather than vigorous vortexing

• Allow sufficient time for complete dissolution before experimental use

Storage Recommendations:

• Upon receipt, immediately store according to manufacturer recommendations

• Use a manual defrost freezer to prevent temperature fluctuations

• Avoid repeated freeze-thaw cycles that can compromise protein integrity

• Working aliquots should be prepared to minimize freeze-thaw events

Stability Considerations:

• The carrier-free (CF) formulation lacks BSA stabilizer, which may affect long-term stability

• When using for cell culture applications, freshly reconstituted protein is optimal

• For analytical standards, protein stability should be verified before critical experiments

Following these guidelines ensures maximum experimental reproducibility and reliable research outcomes when working with this specialized reagent.

How can researchers establish appropriate CHGA expression systems for in vivo studies?

Developing robust CHGA expression systems for in vivo studies requires careful consideration of multiple factors to ensure physiologically relevant outcomes. Based on successful experimental models, researchers should consider the following methodological approach:

Transgenic Model Development:

• Select appropriate bacterial artificial chromosome (BAC) clones containing the complete CHGA gene (~12 kbp) with sufficient flanking sequences

• Consider the extent of flanking sequences when designing constructs, as this significantly impacts expression levels

• Verify integration patterns through PCR analysis using multiple primer sets spanning the gene and flanking regions

• Establish homozygous transgenic lines through systematic breeding strategies

Expression Validation:

• Confirm tissue-specific expression patterns through RT-PCR and immunoblotting

• Quantify circulating CHGA levels using specific ELISA methods

• Perform immunohistochemistry to verify appropriate cellular localization

• Assess functional outcomes through phenotypic analysis

The importance of flanking sequences is particularly evident from comparative studies of humanized CHGA mouse models. For instance, a model with approximately 198 kbp of flanking sequence (Hum CHGA31) demonstrated 14-fold higher circulating CHGA levels compared to a model with only 61 kbp of flanking sequence (Hum CHGA19) . This substantial difference in expression levels directly influenced the ability to rescue disease phenotypes in knockout models, highlighting the critical role of regulatory elements in experimental design.

What methodologies are most effective for studying CHGA's role in stress responses?

Investigating CHGA's role in stress responses requires carefully designed experimental protocols that capture both physiological and molecular endpoints. Based on established research paradigms, the following methodological approaches are recommended:

Immobilization Stress Protocol:

• Obtain necessary animal ethics committee approval following NIH guidelines

• Establish baseline measurements of blood pressure and catecholamine levels

• Implement controlled immobilization using validated restraint apparatus

• Standardize timing (e.g., 2 hours daily between 8:00-10:00 AM) over a defined period (e.g., 21 days)

• Allow appropriate recovery periods (2 hours) before post-stress measurements

• Monitor blood pressure changes twice weekly throughout the experimental period

Molecular Analysis:

• Collect tissue samples from relevant organs (adrenal glands, brain stem)

• Perform quantitative RT-PCR to assess CHGA expression changes

• Conduct immunoblotting to measure protein levels

• Quantify circulating CHGA and catecholamine levels in plasma

• Correlate molecular changes with physiological parameters

Research has demonstrated that mice with different levels of CHGA expression show distinct responses to chronic immobilization stress. While both wild-type and knockout mice may reach similar "ceiling" levels of blood pressure elevation during stress, the baseline and trajectory of these changes differ significantly based on CHGA expression levels . This highlights the importance of temporal monitoring and comprehensive physiological assessment when studying stress-related functions of CHGA.

What techniques can be employed to analyze CHGA promoter regulation and epigenetic modifications?

Understanding CHGA promoter regulation and epigenetic modifications requires sophisticated molecular techniques that can provide insights into transcriptional control mechanisms. Based on published methodologies, researchers should consider the following approach:

CpG Methylation Analysis:

• Extract genomic DNA from CHGA-expressing tissues (e.g., adrenal gland) and non-expressing tissues (e.g., liver)

• Perform bisulfite conversion of isolated DNA

• Design PCR primers to amplify specific promoter regions (e.g., -312 to -157 upstream of ATG)

• Conduct Pyrosequencing to analyze CpG methylation at multiple sites

• Include appropriate controls for methylation status validation

Methylation Controls and Standards:

• Use commercially available control DNA with known methylation levels (low, medium, high)

• Generate standard curves by mixing differentially methylated controls

• Verify PCR bias testing with R² determination (optimal value ≥0.98)

• Include heavily methylated sequence controls (e.g., LINE-1) for assay validation

Comparative Analysis Framework:

• Compare methylation patterns between expressing and non-expressing tissues

• Assess methylation differences between experimental models with varying expression levels

• Correlate methylation status with transcriptional activity

• Examine conservation of regulatory regions across species

Research on humanized CHGA mouse models has revealed that differences in expression between transgenic lines (e.g., Hum CHGA31 vs. Hum CHGA19) are not primarily attributable to differential promoter methylation, as both showed similarly low methylation levels consistent with active promoters. Instead, the presence of additional conserved regulatory sequences in the longer transgene was likely responsible for enhanced expression . This finding underscores the complex nature of CHGA regulation and the importance of comprehensive analysis beyond the proximal promoter region.

How should researchers interpret phenotypic differences in CHGA expression models?

Interpreting phenotypic differences across CHGA expression models requires careful consideration of multiple parameters and potential confounding factors. Researchers should implement the following analytical framework:

Systematic Phenotypic Comparison:

Statistical Analysis Approach:

• Perform ANOVA across all experimental groups for each phenotypic parameter

• Conduct post-hoc Bonferroni-corrected comparisons between specific groups

• Establish significance thresholds appropriate for multiple comparisons

• Consider both statistical significance and biological relevance when interpreting results

Interpretative Considerations:

• Assess dose-response relationships between CHGA expression levels and phenotypic outcomes

• Evaluate the degree of phenotypic rescue in complementation models

• Consider developmental versus acute effects of altered CHGA expression

• Account for potential compensatory mechanisms in chronic models

Research has demonstrated that differences in CHGA expression levels directly correlate with physiological outcomes. For example, Hum CHGA31 mice with 14-fold higher circulating CHGA levels showed complete normalization of blood pressure and catecholamine levels compared to Hum CHGA19 mice, which showed only partial rescue of these parameters . Such findings demonstrate the importance of quantitative analysis in establishing threshold effects and physiological requirements for CHGA function.

What analytical approaches are recommended for assessing CHGA's role in hypertension and cardiovascular regulation?

Investigating CHGA's involvement in hypertension and cardiovascular regulation requires comprehensive analytical approaches that integrate physiological, biochemical, and molecular data. Based on established research paradigms, the following analytical framework is recommended:

Cardiovascular Parameter Assessment:

• Implement longitudinal blood pressure monitoring rather than single time-point measurements

• Compare both systolic and diastolic pressure across experimental groups

• Analyze heart rate variability as an indicator of autonomic function

• Assess cardiovascular responses under both basal and stressed conditions

Catecholamine Dynamics Analysis:

• Measure plasma epinephrine and norepinephrine levels using HPLC with electrochemical detection

• Calculate ratios between different catecholamines to identify synthesis/metabolism alterations

• Correlate catecholamine levels with cardiovascular parameters

• Monitor changes in response to physiological challenges

Gene-Phenotype Correlation:

• Establish quantitative relationships between CHGA expression levels and physiological outcomes

• Determine threshold levels required for normal cardiovascular function

• Identify specific CHGA-derived peptides (e.g., catestatin) that mediate cardiovascular effects

• Compare effects of global versus tissue-specific CHGA alterations

Research with humanized CHGA mouse models has revealed that complete rescue of hypertensive phenotypes requires sufficient expression levels of CHGA. Studies showed that Hum CHGA31 mice with higher expression levels normalized blood pressure comparable to wild-type mice, while Hum CHGA19 mice with lower expression levels remained partially hypertensive . This demonstrates the importance of quantitative assessment and establishing threshold requirements for CHGA's cardiovascular regulatory functions.

How can researchers address challenges in detecting and quantifying CHGA in experimental samples?

Detection and quantification of CHGA in experimental samples can present several technical challenges due to its post-translational modifications, tissue-specific processing, and varying concentrations across biological matrices. The following methodological approaches can help researchers overcome these challenges:

Optimized ELISA Methodology:

• Select appropriate antibody pairs that recognize conserved epitopes (e.g., capturing antibody B4E11)

• Verify species specificity to avoid cross-reactivity issues

• Establish standard curves using recombinant proteins with similar modifications

• Validate assay performance across different biological matrices

Immunoblotting Enhancement:

• Optimize protein extraction buffers based on tissue type

• Adjust SDS-PAGE conditions to accommodate CHGA's molecular weight range (60-80 kDa)

• Implement wet transfer methods with extended duration for large proteins

• Use low-fluorescence membranes to improve signal-to-noise ratio

• Consider chemiluminescent detection for optimal sensitivity

Immunohistochemistry Refinement:

• Test multiple fixation protocols to preserve epitope accessibility

• Implement antigen retrieval techniques appropriate for granin family proteins

• Use chromogen systems with sufficient sensitivity for differential expression analysis

• Include positive and negative tissue controls from verified CHGA expression models

Research has demonstrated that antibody selection significantly impacts detection specificity. For example, studies with humanized CHGA mouse models employed specific ELISA methods that detected only human CHGA without cross-reactivity to mouse samples, enabling precise quantification of transgene expression . Such methodological refinements are essential for reliable comparative analyses across experimental models.

What strategies can resolve data inconsistencies in CHGA functional studies?

When confronted with data inconsistencies in CHGA functional studies, researchers should implement systematic troubleshooting approaches to identify and address potential sources of variability. The following strategies are recommended:

Source Variation Assessment:

• Evaluate genetic background influences in animal models

• Consider age and sex as potential modifying factors

• Assess environmental variables including housing conditions and stress exposure

• Document circadian timing of experiments and sample collection

Methodological Standardization:

• Implement consistent protocols for tissue collection and processing

• Standardize sample preparation procedures across experimental groups

• Calibrate detection instruments regularly and maintain consistent settings

• Establish internal controls for normalization across experiments

Reconciliation Approaches:

• Perform side-by-side comparisons of conflicting models or methodologies

• Consider dose-response relationships rather than binary outcomes

• Analyze temporal dynamics that might explain apparent contradictions

• Implement orthogonal techniques to verify key findings

Statistical Considerations:

• Ensure adequate statistical power through appropriate sample sizes

• Apply normality tests before selecting parametric vs. non-parametric analyses

• Consider multiple testing corrections for comprehensive datasets

• Implement repeated measures designs when appropriate

Research with humanized CHGA mouse models has shown that apparent inconsistencies in phenotypic rescue can often be explained by quantitative differences in expression levels. For example, differential integration of flanking sequences resulted in 14-fold differences in circulating CHGA levels between transgenic lines, which directly correlated with the degree of phenotypic normalization . This highlights the importance of quantitative assessment in resolving apparent functional discrepancies.

What are promising approaches for investigating the therapeutic potential of CHGA-derived peptides?

Investigating the therapeutic potential of CHGA-derived peptides represents a frontier in translational research with significant implications for cardiovascular and metabolic disorders. Based on current understanding and technological capabilities, researchers should consider the following approaches:

Peptide Identification and Optimization:

• Conduct systematic structure-function analyses of CHGA-derived peptides (e.g., catestatin)

• Implement alanine scanning mutagenesis to identify critical residues

• Design modified peptides with enhanced stability or receptor specificity

• Develop delivery systems to improve bioavailability and tissue targeting

Therapeutic Application Assessment:

• Establish dose-response relationships in relevant disease models

• Compare acute versus chronic administration protocols

• Evaluate potential side effects and toxicity profiles

• Investigate combination approaches with established therapies

Mechanistic Investigation:

• Identify cellular receptors and signaling pathways activated by CHGA-derived peptides

• Determine tissue-specific effects through conditional expression models

• Assess effects on multiple physiological systems beyond cardiovascular regulation

• Explore potential interactions with other neuroendocrine pathways

The therapeutic potential of CHGA-derived peptides is supported by research demonstrating that catestatin, a CHGA fragment with catecholamine inhibitory properties, is diminished in hypertensive individuals. Studies with humanized CHGA mouse models have shown that restoring appropriate CHGA levels can normalize blood pressure and catecholamine dynamics in hypertensive phenotypes . These findings suggest that targeted peptide therapies derived from CHGA could offer novel approaches for treating hypertension and related cardiovascular disorders with potentially fewer side effects than current pharmacological interventions.

How might advances in epigenetic analysis enhance our understanding of CHGA regulation?

Advances in epigenetic analysis technologies offer unprecedented opportunities to elucidate the complex regulatory mechanisms controlling CHGA expression in different physiological and pathological contexts. Researchers should consider the following innovative approaches:

Next-Generation Epigenetic Profiling:

• Implement ATAC-seq to map chromatin accessibility across the CHGA locus

• Apply ChIP-seq for histone modification patterns associated with active/repressed states

• Utilize single-cell epigenomic approaches to reveal cell-type-specific regulation

• Employ long-read sequencing to characterize complex regulatory elements

Integrative Multi-Omics Analysis:

• Correlate DNA methylation patterns with transcriptional activity

• Identify transcription factor binding sites through footprinting analysis

• Map three-dimensional chromatin architecture using Hi-C or related techniques

• Integrate genetic variation data to identify functional regulatory polymorphisms

Functional Validation Strategies:

• Apply CRISPR-based epigenome editing to modify specific regulatory elements

• Develop reporter systems for high-throughput screening of regulatory elements

• Create isogenic cell lines with defined epigenetic modifications

• Establish inducible systems to study dynamic epigenetic changes

Current research suggests that CHGA regulation involves complex interactions between multiple regulatory elements beyond the proximal promoter. Studies with humanized CHGA mouse models have shown that differential integration of flanking sequences significantly impacts expression levels, despite similar promoter methylation patterns . These findings highlight the importance of investigating distal regulatory elements and three-dimensional chromatin organization in understanding CHGA regulation. Advanced epigenetic approaches could reveal how these complex regulatory networks are altered in disease states, potentially identifying new targets for therapeutic intervention in conditions associated with dysregulated CHGA expression.