Recombinant Mouse WSC domain-containing protein 2 (Wscd2)

What is Mouse WSC domain-containing protein 2 (Wscd2)?

Wscd2 (UniProt AC: D4PHA7, UniProt ID: WSCD2_MOUSE) is also known as Sialate:O-sulfotransferase 2 in mice. It is encoded by the gene Wscd2 (synonym: Kiaa0789) and is classified in the Protein Ontology database (PRO ID: PR:D4PHA7) as "A WSC domain-containing protein 2 that is encoded in the genome of mouse." The WSC domain is named after Wall integrity and Stress response Component proteins, originally identified in yeast. While the complete functional characterization of Wscd2 remains ongoing, genomic studies have implicated it in personality traits and age-related processes in bone tissue .

What post-translational modifications are known for Wscd2?

Wscd2 undergoes phosphorylation at two specific serine residues: S86 and S230. These modifications have been documented in the PhosphoSitePlus database . Methodologically, researchers investigating these post-translational modifications should employ phospho-specific antibodies for western blotting or immunoprecipitation assays, or mass spectrometry-based phosphoproteomics approaches. While the specific kinases responsible for these phosphorylation events have not been definitively identified in the available data, understanding the regulation of these modifications could provide insights into Wscd2's function in different cellular contexts.

How does Wscd2 expression change with aging in mice?

RNA sequencing analysis of mouse bone tissue across different age points (2 months, 1 year, 2 years, and 2.5 years) revealed that Wscd2 expression significantly decreases with age . Specifically, Wscd2 belongs to cluster 4 of age-related differentially expressed genes (DEGs) identified through time course differential expression analysis using the likelihood ratio test (LRT) in DESeq2 and the degPatterns function in DEGreport package . This downregulation may have functional consequences in age-related bone pathologies, particularly given its association with osteoarthritis. Researchers studying age-related expression changes should employ similar time-course experimental designs with multiple age points to capture the dynamic nature of these changes.

What systems genetics approaches are optimal for studying Wscd2 function in diverse genetic backgrounds?

For comprehensive characterization of Wscd2 function across diverse genetic backgrounds, researchers should implement advanced systems genetics approaches:

• Genetic Reference Populations (GRPs): Utilize established mouse GRPs such as the BXD cohort (derived from C57BL/6J and DBA/2J strains), Hybrid Mouse Diversity Panel (HMDP), or more advanced diversity panels like the Collaborative Cross (CC) and Diversity Outbred (DO) cohorts . These populations capture greater genetic diversity and improve the generalizability of findings.

• Cross-breeding Strategy: Following the methodology demonstrated in previous studies , breed Wscd2 mutant mice with multiple inbred strains (20-30 is optimal) to systematically assess the impact of genetic background on phenotypic manifestations of Wscd2 alterations.

• Sex-specific Analysis: Include balanced groups of male and female mice and perform sex-stratified analyses, as significant sex-specific effects have been observed in similar genetic studies .

• Environmental Challenges: Expose mice to relevant environmental stressors or challenges to reveal phenotypes that may only be apparent under specific conditions.

This comprehensive systems approach will provide insights into how Wscd2 function is modulated by genetic context and improve translatability to human research.

How can the Mouse-to-Human (M2H) strategy be applied to translate Wscd2 findings to human disease research?

The Mouse-to-Human (M2H) strategy has successfully identified Wscd2 as relevant to human osteoarthritis . Researchers can implement this approach through the following methodological steps:

• Differential Expression Analysis: Perform RNA sequencing on mouse tissues across relevant conditions (e.g., aging, disease models) and identify differentially expressed genes (DEGs) using DESeq2, with significance criteria set to FDR < 0.05 .

• Temporal Pattern Clustering: For time-course data, apply the degPatterns function in DEGreport package to cluster genes with similar expression patterns .

• Human Ortholog Mapping: Map mouse DEGs to human orthologs using resources such as the Mouse Genome Informatics database (e.g., HOM_MouseHumanSequence.rpt) .

• GWAS Integration: Apply MAGMA software to determine gene-based scores for human orthologs using published GWAS results, considering variants within 100kb of gene regions and adjusting for linkage disequilibrium, gene density, and gene size .

• Enrichment Analysis: Perform gene set enrichment analysis to determine whether human orthologs of mouse DEGs are enriched for associations with human disease traits .

This systematic approach revealed that Wscd2 is among the 12 genes significantly associated with human knee osteoarthritis after multiple test correction (Bonferroni, adjusted-p < 0.05) , demonstrating its value in translational research.

What bioinformatic pipelines are recommended for analyzing Wscd2 expression changes?

For robust analysis of Wscd2 expression changes, researchers should implement a comprehensive bioinformatic pipeline as demonstrated in previous studies :

• Differential Expression Analysis:

  • Apply DESeq2 package (v.1.24.0) for pairwise comparisons

  • Use Wald test with significance criteria set to Benjamini-Hochberg (BH) FDR < 0.05

  • For time-course data, perform likelihood ratio test (LRT) to identify genes with expression changes across multiple time points

• Expression Pattern Clustering:

  • Implement degPatterns function in DEGreport package (1.30.0) using hierarchical clustering

  • Identify clusters of genes with similar expression patterns across time points

• Pathway Analysis:

  • Conduct over-representation analysis (ORA) using clusterProfiler package (v.3.12.0)

  • Apply compareCluster function to determine enriched KEGG pathways for gene clusters

  • Consider pathways with BH adjusted p-values < 0.05 as significant

• Translational Analysis:

  • Use MAGMA software for gene-based scoring and enrichment analysis

  • Integrate with human GWAS data to assess disease relevance

This methodological framework has successfully identified Wscd2 as part of cluster 4 of age-regulated genes with potential relevance to osteoarthritis .

How should researchers design experiments to investigate Wscd2's role in personality traits?

Based on GWAS findings linking Wscd2 variants to extraversion , researchers investigating its role in personality traits should consider the following experimental design approach:

• Targeted Genetic Modifications:

  • Generate conditional knockout or knockin models specifically targeting the intronic variant rs1426371 that showed significant association with extraversion

  • Use CRISPR-Cas9 or similar technology for precise genetic manipulation

• Behavioral Phenotyping:

  • Implement comprehensive behavioral testing batteries specific to extraversion-related behaviors in mice

  • Include measures of social interaction, exploratory behavior, and response to novelty

  • Assess both approach and avoidance behaviors to capture the full spectrum of extraversion-introversion

• Neural Circuit Analysis:

  • Examine neural activity in brain regions associated with personality traits (e.g., prefrontal cortex, amygdala)

  • Use techniques such as in vivo calcium imaging or electrophysiology during relevant behavioral tasks

• Molecular Pathway Analysis:

  • Investigate Wscd2's interaction with known modulators of extraversion, particularly those involved in dopaminergic and serotonergic signaling

  • Use co-immunoprecipitation and proximity ligation assays to identify protein interaction partners

• Human Correlation Studies:

  • Design translational studies examining WSCD2 expression or genetic variants in human subjects characterized for personality traits

  • Consider using non-invasive methods such as peripheral biomarkers or neuroimaging

This comprehensive approach addresses the observation that personality traits exist along a continuum from internalizing (e.g., neuroticism, depression, anxiety) to externalizing traits, which correlate with Principal Component 2 (PC2) closely aligned with extraversion-introversion .

What strategies can researchers employ to generate and validate recombinant mouse Wscd2 protein?

For successful production and validation of recombinant mouse Wscd2 protein, researchers should implement the following methodological approach:

• Expression System Selection:

  • For mammalian post-translational modifications, use HEK293 or CHO cell systems

  • For high yield protein production, consider baculovirus-insect cell or E. coli systems with subsequent refolding if necessary

• Construct Design:

  • Include the complete coding sequence of mouse Wscd2

  • Add appropriate affinity tags (His, FLAG, or GST) for purification

  • Consider including specific phosphorylation sites (S86 and S230) based on known post-translational modifications

  • Design constructs with and without WSC domains to assess domain-specific functions

• Purification Strategy:

  • Implement a two-step purification process combining affinity chromatography and size exclusion chromatography

  • Monitor protein purity using SDS-PAGE and western blotting

• Functional Validation:

  • Verify proper folding using circular dichroism spectroscopy

  • Assess enzymatic activity based on its annotation as Sialate:O-sulfotransferase 2

  • Evaluate phosphorylation status using phospho-specific antibodies or mass spectrometry

• Interaction Studies:

  • Perform pull-down assays to identify binding partners

  • Use surface plasmon resonance to quantify binding kinetics with potential interactors

This systematic approach will generate high-quality recombinant Wscd2 protein suitable for downstream biochemical and structural studies.

How can researchers interpret contradictory findings in Wscd2 functional studies across different genetic backgrounds?

When faced with contradictory findings in Wscd2 functional studies across different genetic backgrounds, researchers should implement the following analytical framework:

• Genetic Background Analysis:

  • Recognize that genetic mutations can have varying or even opposite effects depending on the genetic background

  • Document and report the specific genetic background used in each experiment with complete strain information

  • Consider quantitative trait locus (QTL) mapping to identify modifier genes that may interact with Wscd2

• Experimental Design Considerations:

  • Replicate key experiments across multiple genetic backgrounds

  • Use genetic reference populations (GRPs) like the BXD cohort or Collaborative Cross to systematically assess background effects

  • Include both sexes in analyses, as sex-specific effects have been observed in various mouse models

• Data Integration Methods:

  • Apply meta-analysis techniques to quantitatively combine results across studies

  • Use systems genetics approaches to place contradictory findings in the context of broader gene networks

  • Consider Bayesian statistical frameworks that can incorporate prior knowledge from diverse studies

• Contextual Interpretation:

  • Evaluate whether contradictions stem from methodological differences versus true biological variation

  • Examine environmental factors and experimental conditions that may interact with genetic background

  • Consider that contradictory findings may reflect real biological complexity rather than experimental error

This approach aligns with observations from multiple systems genetics studies showing that the impact of specific gene mutations varies widely across different genetic backgrounds , highlighting the importance of genetic context in understanding gene function.

What are the optimal conditions for detecting Wscd2 phosphorylation in mouse tissue samples?

To effectively detect Wscd2 phosphorylation at S86 and S230 sites , researchers should implement the following protocol:

• Tissue Sample Preparation:

  • Harvest tissues rapidly and flash-freeze in liquid nitrogen

  • Include phosphatase inhibitor cocktails in all extraction buffers

  • Lyse tissues in buffer containing 50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 1 mM EDTA, 1 mM PMSF, phosphatase inhibitors (10 mM NaF, 1 mM Na3VO4, 10 mM β-glycerophosphate)

• Enrichment Strategies:

  • Perform immunoprecipitation using Wscd2-specific antibodies

  • Alternatively, use phospho-peptide enrichment methods such as TiO2 or IMAC prior to mass spectrometry analysis

• Detection Methods:

  • Western blotting with phospho-specific antibodies against pS86 and pS230

  • Phospho-proteomic mass spectrometry using parallel reaction monitoring (PRM) for targeted analysis

  • Phos-tag SDS-PAGE to resolve phosphorylated from non-phosphorylated forms

• Validation Approaches:

  • Include lambda phosphatase treatment controls

  • Generate phospho-mimetic (S to D/E) and phospho-null (S to A) mutants for functional studies

This methodology will enable sensitive and specific detection of Wscd2 phosphorylation states, facilitating research into their functional significance.

How should researchers design experiments to study the association between Wscd2 and osteoarthritis?

Based on the significant association between Wscd2 and knee osteoarthritis , researchers should implement the following experimental design:

• Animal Models:

  • Generate conditional Wscd2 knockout mice specifically in cartilage (using Col2a1-Cre) and bone (using Osx-Cre)

  • Subject these models to established OA induction protocols (surgical destabilization of the medial meniscus or collagenase injection)

  • Include aging cohorts to assess natural development of OA in relation to Wscd2 expression

• Molecular Analyses:

  • Perform RNA-seq and proteomics on joint tissues at multiple time points

  • Focus on the subchondral bone plate (SBP), as its thickness significantly increases by 18-months of age, corresponding with increased cartilage degeneration

  • Implement the M2H strategy to correlate findings with human GWAS data

• Histological Assessments:

  • Conduct comprehensive histomorphometric analysis of joint tissues

  • Employ standardized scoring systems for OA severity

  • Use immunohistochemistry to localize Wscd2 expression in joint tissues

• Translational Approaches:

  • Analyze Wscd2 expression in human OA tissues compared to healthy controls

  • Genotype human OA patients for WSCD2 variants

  • Develop in vitro models using human chondrocytes and osteoblasts with WSCD2 knockdown/overexpression

This systematic approach will provide insights into the mechanistic role of Wscd2 in OA pathogenesis, particularly in the context of bone-cartilage crosstalk during aging.

Table: Mouse genes and their human orthologs significantly associated with knee osteoarthritis based on the Mouse-to-Human (M2H) strategy

What statistical approaches should be used when analyzing Wscd2 expression across different experimental conditions?

For robust statistical analysis of Wscd2 expression data, researchers should implement the following methodological framework:

• Differential Expression Analysis:

  • For RNA-seq data, use DESeq2 with appropriate design formulas that account for relevant covariates

  • Apply Wald test for pairwise comparisons and likelihood ratio test (LRT) for time-course experiments

  • Set significance threshold at FDR < 0.05 using Benjamini-Hochberg correction

• Temporal Pattern Analysis:

  • Implement hierarchical clustering of temporal expression profiles using degPatterns function

  • Consider non-linear mixed effects models for complex temporal patterns

  • Visualize expression changes using heatmaps and trajectory plots

• Multi-omics Integration:

  • Correlate Wscd2 expression with other molecular data (proteomics, metabolomics)

  • Use weighted gene co-expression network analysis (WGCNA) to identify co-regulated gene modules

  • Apply causal inference methods to establish directional relationships

• Correction for Confounding Factors:

  • Account for batch effects using ComBat or similar methods

  • Consider tissue heterogeneity using deconvolution approaches

  • Include relevant biological variables (age, sex, genetic background) in statistical models

This comprehensive statistical approach has been successfully applied in previous studies identifying Wscd2 as part of cluster 4 of age-regulated genes with potential relevance to osteoarthritis .

How can researchers effectively integrate Wscd2 findings with broader systems biology frameworks?

To maximize the impact of Wscd2 research within systems biology frameworks, researchers should implement the following integrative approach:

• Network Analysis:

  • Construct gene regulatory networks centered on Wscd2 using weighted gene co-expression network analysis (WGCNA)

  • Identify hub genes and modules that interact with Wscd2 under relevant conditions

  • Map Wscd2 onto existing protein-protein interaction networks

• Pathway Enrichment:

  • Perform over-representation analysis (ORA) using clusterProfiler to identify enriched KEGG pathways

  • Apply gene set enrichment analysis (GSEA) to determine whether Wscd2-associated genes are enriched in specific biological processes

  • Consider tissue-specific pathway annotations for contextual interpretation

• Multi-species Integration:

  • Implement the Mouse-to-Human (M2H) strategy to translate findings across species

  • Use resources like HOM_MouseHumanSequence.rpt for ortholog mapping

  • Apply comparative genomics approaches to identify evolutionarily conserved functions

• Dimensionality Reduction:

  • Use principal component analysis (PCA) to place Wscd2 within the broader context of disease-associated genes

  • Consider the observation that PC2 is closely aligned with extraversion-introversion traits, which have been associated with Wscd2

  • Apply t-SNE or UMAP for non-linear visualization of complex relationships