VSNL1 Human, His

What is the basic structure and function of VSNL1/VILIP-1 in the human nervous system?

VSNL1 (visinin-like 1), also known as VILIP-1, is a member of the neuronal EF-hand Ca²⁺-sensor protein family. It plays crucial roles in neuronal function by influencing cytosolic cyclic adenosine monophosphate (cAMP) levels, cell migration, exocytotic processes, and neuronal differentiation . The protein was initially identified during developmental screening as upregulated in the chick visual cortex, showing enhanced expression during neuronal differentiation and axonal pathfinding .

Experimentally, VSNL1 has been demonstrated to regulate cAMP signaling in neurons - knockdown experiments show decreased cAMP levels and reduced dendrite branching, while overexpression produces opposite effects . This strongly suggests VSNL1's involvement in neuronal morphology development through cAMP-dependent pathways.

Methodologically, researchers study VSNL1 function using:

• RNA interference (siRNA knockdown)

• Overexpression studies

• Pharmacological manipulation of associated pathways

• Morphological analysis of neurite development

• cAMP level quantification

How do histidine tags affect VSNL1 protein function in experimental settings?

When designing experiments with His-tagged VSNL1, researchers should consider:

• Tag position effects: N-terminal versus C-terminal His-tags may differentially impact protein folding and function

• Purification strategy: Optimizing imidazole concentration gradients during elution to maintain protein activity

• Tag interference assessment: Comparing tagged and untagged protein activity in functional assays

• Calcium-binding validation: Ensuring the His-tag doesn't interfere with VSNL1's calcium-sensing properties

• Structure confirmation: Using circular dichroism or other structural analysis to verify proper folding

What is the evidence linking VSNL1 gene variants to schizophrenia?

Multiple studies have demonstrated significant associations between VSNL1 single-nucleotide polymorphisms (SNPs) and schizophrenia. Both intergenic SNPs (rs394874 and rs424827) located on chromosome 2p24.3 and intragenic SNPs (rs650275, rs834504, rs1519477, rs12470654, rs1033297, and rs11677051) show significant association with schizophrenia (p=0.0080, p=0.0097, p=0.0178, p=0.0190, p=0.0210, p=0.0054, p=0.0384 and p=0.0053, respectively) .

Haplotype analysis has further confirmed these case-control results, revealing one haplotype (CGTCTAAG) with higher frequency in schizophrenia patients (27.7% vs 24.0% in controls, χ²=4.034, p=0.0446) and a protective haplotype (TACTCGGA) occurring less frequently in patients (23.7% vs 28.2% in controls, χ²=6.155, p=0.0131) .

Additionally, VSNL1 SNPs associate with performance on the Wisconsin Card Sorting Test, a sensitive measure of frontal cortical function that is typically impaired in schizophrenia . This suggests VSNL1's potential role in cognitive aspects of the disorder.

For researchers studying this association, methodological approaches should include:

• Genotyping with high-quality platforms like Illumina BeadChip

• Adequate sample sizes for detecting subtle genetic effects

• Control for population stratification

• Functional validation of SNP effects on VSNL1 expression/activity

• Investigation of specific endophenotypes rather than broad diagnoses

How can researchers effectively study VSNL1's role in neurodegenerative processes?

VSNL1/VILIP-1 has been implicated in neurodegenerative processes, particularly Alzheimer's disease (AD), with evidence suggesting it may contribute to AD pathophysiology through altered expression or by affecting processes related to synapse or neuronal loss .

To effectively study VSNL1's role in neurodegeneration, researchers should implement a multifaceted approach:

• Expression analysis:

  • Quantify VSNL1 expression in different brain regions across age groups

  • Control for technical factors that significantly affect measurements (pH: p=7.21e-09 in BA11; RIN: p=3.66e-12 in BA11)

  • Analyze co-expression patterns with known neurodegeneration-related genes

• Protein quantification:

  • Use sensitive ELISA methods (detection limit 18.75pg/ml) for CSF/plasma measurements

  • Compare levels between healthy controls and patients with neurodegenerative disorders

  • Conduct longitudinal studies tracking VSNL1 levels over disease progression

• Co-expression network analysis:

  • Examine age-stratified networks (under vs. over 50 years)

  • Focus on KEGG pathways for calcium signaling and AD that are enriched in VSNL1 networks

  • Investigate shifts in co-expression partners with age and disease status

• Functional studies:

  • Assess VSNL1's impact on calcium homeostasis in neuronal models

  • Investigate effects on synaptic function and neuronal survival

  • Examine interaction with known pathological processes (amyloid, tau)

What are the optimal methods for quantifying VSNL1 expression in human brain samples?

When quantifying VSNL1 expression in human brain samples, researchers should consider several methodological factors to ensure accurate and reliable results:

• Sample collection and preservation:

  • Control for post-mortem interval (though PMI shows non-significant association with VSNL1 expression: p=0.26 in BA11)

  • Maintain consistent pH (significant impact: p=7.21e-09 in BA11)

  • Assess RNA integrity number (RIN) (significant impact: p=3.66e-12 in BA11)

• mRNA quantification:

  • Use RT-qPCR with validated reference genes

  • Include technical and biological replicates

  • Control for age, sex, and race (though these factors show no significant association with VSNL1 expression)

• Protein quantification:

  • Western blot analysis with anti-VILIP-1 antibodies and anti-actin controls

  • ELISA with sensitivity range of 31.25-2000pg/ml

  • Consider regional specificity in expression patterns

• Statistical analysis:

  • Apply linear regression models to control for technical covariates

  • Consider age stratification for co-expression analysis

  • Test for interactions between demographic and technical factors

A comprehensive experimental design might include:

• Multiple brain regions (not limited to frontal cortex)

• Age-stratified cohorts (16-91 years range is recommended)

• Balanced representation across demographic variables (79% male, 85% Caucasian in reference studies)

• Detailed recording of technical parameters (mean pH: 6.7±0.3; mean RIN: 8.0±0.73)

What are the best experimental approaches for analyzing VSNL1's effects on neuronal morphology?

To effectively analyze VSNL1's effects on neuronal morphology, researchers should employ sophisticated quantitative approaches that capture both gross and subtle changes in neuronal structure:

• Cell culture models:

  • Primary rat hippocampal neurons (for physiological relevance)

  • Human dopaminergic SH-SY5Y neuronal cell line (for human-specific effects)

  • Consider density of plating (recommended: 60,000 hippocampal neurons for western blot analysis)

• Molecular manipulation techniques:

  • VILIP-1 siRNA knockdown (assess efficiency via western blot)

  • Overexpression via appropriate vectors

  • Pharmacological manipulation with adenylyl cyclase inhibitor (2′,5′-dideoxyadenosine) or protein kinase A inhibitor (KT5720)

• Morphological analysis methods:

  • Sholl analysis: Quantify dendritic branching by counting intersections with concentric circles at increasing radii (20-100μm) from the soma

  • NeuronJ plugin with ImageJ software: Measure neurite number and length (specifically neurites longer than one cell diameter)

  • Time-course analysis: Examine neurons at different time points post-transfection (e.g., 48 hours)

• Imaging and quantification:

  • Use consistent image acquisition parameters

  • Analyze sufficient numbers of neurons per condition

  • Blind the analysis process to prevent bias

  • Include appropriate statistical comparisons

This experimental design allows researchers to determine whether VSNL1 affects:

• Total dendritic length

• Branching complexity

• Branch point distribution

• Growth dynamics

• Response to pharmacological manipulation of cAMP pathway

How can researchers resolve contradictions in VSNL1 co-expression networks across different age groups?

Contradictions in VSNL1 co-expression networks between age groups represent a complex research challenge requiring sophisticated approaches:

• Age-stratified analysis:

  • Separate co-expression networks for different age groups (under vs. over 50 years)

  • Examine the 400 genes with the greatest positive and negative correlations with VSNL1 in each age group

  • Perform differential co-expression analysis between age groups

• Technical considerations:

  • Control for brain pH (p=7.21e-09 in BA11) and RIN (p=3.66e-12 in BA11)

  • Standardize tissue collection and processing

  • Validate findings across multiple brain regions (e.g., BA11 and BA47)

• Statistical approaches:

  • Use weighted gene co-expression network analysis (WGCNA)

  • Apply multivariate models to account for confounding variables

  • Implement network comparison statistics to quantify differences

• Biological validation:

  • Confirm key relationships through independent techniques

  • Test whether identified differences are functionally relevant

  • Investigate if changes reflect altered cellular composition vs. molecular interactions

• Experimental testing:

  • Manipulate VSNL1 expression in young vs. aged neuronal cultures

  • Assess impact on identified co-expression partners

  • Determine whether age-dependent effects are mechanistically different

This comprehensive approach can help determine whether apparent contradictions stem from biological reality or methodological differences, with important implications for understanding VSNL1's role in normal aging and pathological conditions.

What experimental design best captures VSNL1's calcium-dependent regulation of cAMP signaling?

To effectively capture VSNL1's calcium-dependent regulation of cAMP signaling, researchers should implement a comprehensive experimental design that integrates multiple approaches:

• Real-time monitoring system:

  • FRET-based cAMP sensors for continuous measurement

  • Simultaneous calcium imaging using spectrally distinct indicators

  • Time-resolved correlation between calcium fluctuations and cAMP dynamics

• Genetic manipulation approach:

  • VSNL1 knockdown via siRNA (validate 48 hours post-transfection)

  • Overexpression of wild-type VSNL1

  • Expression of calcium-binding-deficient VSNL1

  • Control transfections for comparison

• Pharmacological dissection:

  • Adenylyl cyclase inhibitor (2′,5′-dideoxyadenosine) to block cAMP production

  • Protein kinase A inhibitor (KT5720) to suppress downstream signaling

  • Calcium chelators and ionophores to manipulate calcium levels

  • Combined treatments to establish hierarchy of effects

• Downstream readouts:

  • cAMP-dependent morphological changes (dendrite branching in hippocampal neurons)

  • PKA substrate phosphorylation

  • CREB phosphorylation and transcriptional activation

  • Electrophysiological consequences

• Analytical considerations:

  • Dose-response relationships for calcium dependency

  • Temporal dynamics of calcium-cAMP coupling

  • Regional differences in neuronal responsiveness

  • Developmental stage influence on signaling efficiency

This multifaceted approach will reveal not just whether VSNL1 regulates cAMP levels in response to calcium, but also the quantitative parameters, spatiotemporal dynamics, and downstream consequences of this regulation in neuronal contexts.

How can VSNL1 biomarker development be optimized for neurological disorders?

Optimizing VSNL1 as a biomarker for neurological disorders requires addressing several methodological challenges:

• Assay development considerations:

  • Standardize ELISA protocols with sensitivity in the 18.75pg/ml range

  • Establish detection ranges appropriate for clinical samples (31.25-2000pg/ml)

  • Validate across different biological matrices (CSF, plasma, serum)

  • Implement quality control procedures for clinical laboratory settings

• Clinical validation approach:

  • Define precise neurological conditions where VSNL1 has diagnostic value

  • Design studies with adequate statistical power for biomarker validation

  • Include longitudinal sampling to assess prognostic capabilities

  • Correlate with established biomarkers and clinical outcomes

• Genetic influence assessment:

  • Determine how VSNL1 SNPs associated with schizophrenia affect protein levels

  • Investigate whether risk haplotypes (CGTCTAAG) versus protective haplotypes (TACTCGGA) show differential biomarker patterns

  • Develop genotype-informed interpretation guidelines

• Technical challenges:

  • Ensure antibody specificity across VSNL1 isoforms

  • Address potential confounding factors (medications, comorbidities)

  • Establish age-appropriate reference ranges

  • Standardize sample collection and processing procedures

• Analytical considerations:

  • Determine appropriate cutoff values for clinical decision-making

  • Evaluate biomarker performance in combination panels

  • Develop algorithms integrating VSNL1 with other markers

  • Assess cost-effectiveness of implementation

This systematic approach will help establish whether VSNL1 meets criteria for clinical utility as a biomarker while addressing the technical and biological complexities inherent in neurological disorder diagnostics.

What methodological approaches can best elucidate VSNL1's role in synaptic pathology related to Alzheimer's disease?

To elucidate VSNL1's role in synaptic pathology related to Alzheimer's disease (AD), researchers should implement a comprehensive methodological framework:

• Co-expression network analysis approach:

  • Analyze VSNL1 within KEGG pathways for calcium signaling and AD

  • Compare networks between normal aging and AD brain tissue

  • Focus on pathways implicated in synaptic pathology in AD

  • Examine age-stratified networks (under vs. over 50 years)

• Cellular and subcellular localization studies:

  • Assess VSNL1 distribution at synapses using super-resolution microscopy

  • Examine colocalization with synaptic markers in control vs. AD tissue

  • Track calcium-dependent translocation in neuronal models

  • Compare subcellular distribution in different stages of AD pathology

• Functional impact assessment:

  • Measure effects of VSNL1 manipulation on synaptic transmission

  • Evaluate influence on synaptic plasticity mechanisms

  • Assess interaction with amyloid-β and tau pathology

  • Quantify impact on dendritic spine morphology and density

• Model systems approach:

  • Human post-mortem tissue with varying Braak stages

  • iPSC-derived neurons from AD patients vs. controls

  • Transgenic AD mouse models with VSNL1 overexpression/knockdown

  • Organoid models to capture complex cellular interactions

• Intervention studies:

  • Test whether modulating VSNL1 function affects synaptic resilience

  • Assess potential for calcium signaling-based therapeutic approaches

  • Determine critical windows for intervention in disease progression

  • Evaluate combination approaches targeting multiple pathways

This multifaceted approach will help determine whether VSNL1 represents a contributor to AD-related synaptic dysfunction, a compensatory response, or a biomarker of the underlying pathological process, with important implications for therapeutic development.