Nuclear staining and relative distance for quantifying epidermal differentiation in biomarker expression profiling

Area of Science:

• Dermatology and skin biology
• Computational biology and bioinformatics
• Biophysics and mathematical modeling

Background:

• Epidermal homeostasis relies on regulated keratinocyte proliferation, differentiation, and death.
• Understanding epidermal physiology necessitates integrating differentiation-dependent protein expression into biological models.
• Accurate quantification of tissue differentiation and biomarker correlation is crucial for in silico modeling.

Purpose of the Study:

• To develop and evaluate mathematical measures for quantifying epidermal keratinocyte differentiation.
• To integrate these measures with immunofluorescence staining and image analysis for automated quantification.
• To correlate quantitative differentiation with the expression of differentiation-related biomarkers.

Main Methods:

• Designed and evaluated three mathematical measures: nuclei-based, distance-based, and a joint approach.
• Integrated measures with immunofluorescent staining and automated image analysis of epidermal tissue sections.
• Quantified epidermal differentiation and measured corresponding biomarker expression in a human neck skin sample.

Main Results:

• The distance-based and joint approaches, incorporating cell-to-border distance, provided high-resolution profiles of keratinocyte differentiation.
• The nuclei density approach showed increased resolution at early but decreased resolution at late differentiation stages.
• Non-linear decay of DAPI intensity per area, likely due to cytoplasmic growth, affected nuclei density measures.

Conclusions:

• Tissue homeostasis mechanisms may rely more on distance information than nuclei reorganization.
• The distance-based approach is well-suited for comprehensive observation of keratinocyte differentiation.
• This method enables high-resolution quantitative analysis of epidermal differentiation and biomarker expression.