SRGN Human, HEK

What is SRGN and what are its significant functions in human vascular biology?

SRGN (Serglycin) is a proteoglycan that has been identified as a key shear-stress-responsive gene in endothelial cells. Research has shown that SRGN plays an important role in the pathogenesis of cardiovascular disease, particularly atherosclerosis (AS). It appears to be upregulated under low shear stress conditions and may be involved in endothelial cell proliferation. Studies indicate that SRGN expression is significantly increased in atherosclerotic plaques induced by abnormal shear stress, suggesting it functions as a mechanosensitive gene that helps endothelial cells respond to wall shear stress (WSS) .

How is SRGN expression regulated in endothelial cells under different shear stress conditions?

SRGN expression is regulated through the PKA/CREB-dependent signaling pathway in response to shear stress. Specifically, low shear stress (LSS) enhances SRGN expression via this pathway in human umbilical vein endothelial cells (HUVECs). The experimental evidence demonstrates a direct relationship between mechanical forces and SRGN expression levels, where abnormal wall shear stress triggers increased SRGN production. This mechanotransduction mechanism represents an important link between biomechanical forces and gene expression in the vascular system .

What experimental evidence links SRGN to endothelial cell proliferation?

Studies examining SRGN in HUVECs have demonstrated that cells with high SRGN expression show increased proportions of Ki67+ cells, a marker of cellular proliferation. Additionally, these cells exhibit higher concentrations of nitric oxide (NO), suggesting multiple pathways through which SRGN may influence endothelial cell behavior. These findings indicate that SRGN is not merely responding to shear stress but actively participating in cellular processes that may contribute to vascular remodeling and disease progression .

What cell culture systems are optimal for studying SRGN expression in recombinant systems?

These differences highlight the importance of bioreactor selection based on the specific research objectives and desired properties of the recombinant serglycin .

What in vivo models are effective for investigating SRGN's role in atherosclerosis?

The partial ligation of carotid artery in mice serves as an effective model for studying SRGN's role in atherosclerosis. This model creates regions of abnormal shear stress, triggering the formation of atherosclerotic plaques where SRGN expression is significantly increased. This approach allows researchers to examine the spatial and temporal patterns of SRGN expression in relation to plaque development, providing insights into the mechanistic role of SRGN in atherosclerosis progression under physiologically relevant conditions .

What methodological approaches are most effective for identifying shear-stress-responsive genes like SRGN?

Bioinformatics analysis of high-throughput data from models before and after blood flow formation has proven effective for identifying mechanosensitive genes like SRGN. The methodology involves:

• Analysis of differential gene expression in multiple datasets (e.g., GSE126617 and GSE20707 in the GEO database)

• Selection of common differentially expressed genes across datasets

• Verification through in vitro shear stress loading experiments with HUVECs

• Validation using in vivo models such as partial ligation of carotid artery in mice

This multi-step approach combining computational analysis with experimental validation provides robust identification of mechanosensitive genes like SRGN .

How does the PKA/CREB signaling pathway mediate SRGN expression under shear stress conditions?

The PKA/CREB signaling pathway serves as a critical mediator of SRGN expression in response to low shear stress. The current understanding suggests a sequential activation process:

• Low shear stress conditions trigger increased intracellular cAMP levels

• Elevated cAMP activates Protein Kinase A (PKA)

• Activated PKA phosphorylates CREB (cAMP Response Element-Binding protein)

• Phosphorylated CREB binds to the promoter region of the SRGN gene

• This binding enhances SRGN transcription and subsequent protein expression

This pathway represents a direct mechanistic link between mechanical forces experienced by endothelial cells and the transcriptional regulation of SRGN .

What is the relationship between SRGN expression and fibroblast growth factor 2 (FGF2) signaling?

SRGN produced in tissue culture flasks demonstrates effective binding and signaling of fibroblast growth factor 2 (FGF2). This interaction is particularly significant as FGF2 is involved in various cellular processes including proliferation, differentiation, and angiogenesis. The binding efficacy appears to depend on the sulfation pattern of the heparin/heparan sulfate chains attached to the serglycin core protein. More highly-sulfated heparin/heparan sulfate chains, characteristic of serglycin produced in tissue culture flasks, show enhanced FGF2 binding and downstream signaling capabilities. This finding highlights SRGN's potential role in modulating growth factor activity within the vascular environment .

How does SRGN contribute to the pathophysiology of atherosclerosis at the molecular level?

SRGN's contribution to atherosclerosis pathophysiology involves multiple molecular mechanisms:

• Mechanosensing: SRGN expression increases in response to abnormal (low) shear stress, an early trigger for atherosclerotic plaque formation

• Proliferative Effects: Increased SRGN correlates with higher Ki67+ cell proportions, suggesting a role in endothelial proliferation

• Nitric Oxide Modulation: SRGN high-expression cells show increased NO concentration, potentially affecting vascular tone and endothelial function

• Growth Factor Interactions: SRGN binds and modulates FGF2 signaling, which may influence vascular remodeling

• Plaque Development: Significantly increased SRGN expression is observed in atherosclerotic plaques induced by abnormal shear stress

These molecular mechanisms collectively suggest that SRGN acts as both a sensor and effector in the atherosclerotic process, linking mechanical forces to cellular responses that contribute to disease progression .

What bioinformatic strategies are most effective for analyzing SRGN expression in high-throughput datasets?

For robust analysis of SRGN expression in high-throughput datasets, a multi-method approach is recommended:

For maximum reliability, researchers should focus on consistent results across multiple methods, as demonstrated in studies examining differentially expressed genes during developmental processes .

How can single-cell RNA sequencing enhance our understanding of SRGN expression heterogeneity?

Single-cell RNA sequencing (scRNA-seq) offers several advantages for studying SRGN expression:

• Reveals cell-to-cell variability in SRGN expression that might be masked in bulk analyses

• Enables identification of specific cell subpopulations with distinct SRGN expression patterns

• Allows temporal tracking of SRGN expression changes at single-cell resolution during developmental processes

• Facilitates the integration of SRGN expression data with broader transcriptional networks

• Enables the construction of gene regulatory networks to understand SRGN's place in cellular response systems

These capabilities make scRNA-seq particularly valuable for understanding the heterogeneous expression of mechanosensitive genes like SRGN across different vascular cell populations and states .

What statistical considerations are critical when analyzing SRGN expression under different experimental conditions?

When analyzing SRGN expression under different experimental conditions, researchers should consider:

• Sample Size Determination: Calculate appropriate sample sizes to achieve sufficient statistical power for detecting meaningful changes in SRGN expression

• Normalization Methods: Select appropriate normalization strategies to account for technical variations while preserving biological signals

• Multiple Testing Correction: Apply methods like Benjamini-Hochberg procedure to control false discovery rates when examining SRGN across multiple conditions

• Effect Size Estimation: Focus on fold-change thresholds and the magnitude of expression differences, not just statistical significance

• Validation Across Methods: Use multiple statistical methods (MAST, Limma, DESeq2) and focus on consistently identified changes

• Biological Replicates: Prioritize biological over technical replicates to capture true biological variability in SRGN responses

These considerations ensure robust and reproducible analyses of SRGN expression patterns under different experimental conditions .

What factors influence the production and glycosylation of recombinant SRGN in HEK cell systems?

Several key factors influence recombinant SRGN production and glycosylation in HEK cell systems:

Understanding these factors allows researchers to tailor their production systems to achieve desired SRGN characteristics for specific research applications .

How can researchers overcome variability in SRGN expression when studying mechanotransduction?

To overcome variability in SRGN expression studies focusing on mechanotransduction:

• Standardize Flow Conditions: Use precise flow chambers or parallel-plate systems with controlled parameters for shear stress application

• Cell Synchronization: Ensure cells are at similar passage numbers and cell cycle stages

• Time-Course Analysis: Capture the dynamic nature of SRGN responses through careful temporal sampling

• Multiple Readouts: Assess SRGN expression at mRNA and protein levels with quantitative techniques

• Internal Controls: Include mechanosensitive genes with well-characterized responses as positive controls

• Biological Replicates: Perform experiments with cells from multiple donors when using primary cells

• Pathway Inhibitors: Use specific inhibitors of the PKA/CREB pathway to confirm mechanistic relationships

These approaches help minimize experimental noise and enhance detection of true biological effects in mechanotransduction studies involving SRGN .

What are the critical considerations for translating SRGN research findings from HEK cell models to primary human cells?

When translating SRGN research findings from HEK cell models to primary human cells, researchers should consider:

• Cell Type Differences: HEK-293 cells have different baseline expression levels and regulatory mechanisms compared to primary endothelial cells

• Glycosylation Machinery: Variations in glycosylation enzymes between HEK cells and primary cells may affect SRGN structure and function

• Signaling Context: The PKA/CREB pathway may interact differently with other signaling networks in different cell types

• Response Kinetics: Primary cells may exhibit different temporal dynamics in SRGN expression compared to HEK cells

• Physiological Relevance: Validate key findings in primary cells under conditions that better recapitulate in vivo environments

• Donor Variability: Account for genetic and epigenetic variations when using primary cells from different donors

• Integration with In Vivo Models: Combine in vitro findings with appropriate animal models like the partial carotid ligation model

A systematic approach addressing these considerations helps ensure that insights gained from HEK cell systems accurately reflect SRGN biology in primary human cells and tissues .

How might single-cell transcriptomics advance our understanding of SRGN's role in vascular pathophysiology?

Single-cell transcriptomics offers promising avenues for advancing SRGN research in vascular pathophysiology:

• Identifying specific vascular cell populations with differential SRGN expression in atherosclerotic plaques

• Mapping the temporal dynamics of SRGN expression during atherosclerosis progression

• Uncovering co-expression patterns between SRGN and other mechanosensitive genes

• Revealing cell-specific regulatory networks governing SRGN expression

• Characterizing the heterogeneity of SRGN responses to different mechanical stimuli across vascular cell types

These approaches could provide unprecedented resolution of SRGN's role in vascular disease and potentially identify new therapeutic targets within the mechanotransduction pathway .

What potential therapeutic applications might emerge from understanding SRGN's role in shear stress responses?

Understanding SRGN's role in shear stress responses could lead to several therapeutic applications:

• Targeted Interventions: Developing small molecules or biologics that modulate SRGN expression or function in regions prone to atherosclerosis

• Biomarkers: Using SRGN expression patterns as predictive biomarkers for vascular regions at risk for atherosclerotic development

• Biomaterial Design: Engineering vascular grafts or stents that control local SRGN expression to promote favorable endothelial responses

• Drug Delivery: Utilizing SRGN's growth factor binding properties for targeted delivery of therapeutic agents

• Regenerative Medicine: Exploiting SRGN's role in endothelial proliferation for vascular repair strategies

These applications represent promising directions for translating mechanistic insights about SRGN into clinical interventions for vascular diseases .

How might integrating SRGN studies with other omics approaches enhance our understanding of mechanotransduction in vascular biology?

Integrating SRGN studies with multi-omics approaches could provide comprehensive insights into mechanotransduction: