Comprehensive Methodologies for Diverse Skin Tissue Analysis

This study employed a rigorous and multi-faceted approach to investigate skin samples across a broad spectrum of species and developmental stages, utilizing advanced histological, molecular, and computational techniques.

Tissue Sample Collection and Processing

Skin samples were meticulously collected from a diverse range of adult and neonatal species. These included naked mole rats, rhesus macaques, common marmosets, various dolphin species (bottlenose, long-beaked common, short-beaked common), North American grizzly bears, multiple mouse strains (WT C57BL/6, K14-Cre;Lef1fl/fl, K14-CreERT;Bmpr1afl/fl, K14-CreERT), humans (gestational and adult), and several pig types (E90, P3, P10, 6mo, EDA-KO, Yucatan miniature hairless, Hanford miniature, Mangalitsa).

Samples were sourced from various anatomical locations, such as back skin, trunk skin, dorsal rump, digits, and surgical discards.

All animal studies rigorously adhered to approved Institutional Animal Care and Use Committee (IACUC) protocols, while human tissue collection followed Institutional Review Board (IRB) approved protocols with informed maternal or patient consent.

Tissue preservation involved fixation in 4% paraformaldehyde (PFA) or 10% neutral buffered formalin, followed by storage in 70% ethanol or cryopreservation in OCT at -80 °C.

Histological Analysis

Paraffin-embedded tissues were precisely sectioned at 5 μm or 10 μm. Cryo-preserved samples underwent sectioning at 10-15 μm. Sections were then stained using Hematoxylin and Eosin (H&E) or Herovici’s polychrome. Coverslips were mounted using either Permount or DPX.

Imaging was performed using a suite of advanced microscopes, including the Nikon Eclipse E600, Keyence BZ-X810, Leica cryostat, Olympus FV3000, Leica SP5/SP8 confocal, and Leica DMI8 systems.

Specialized Porcine Studies

Wound Healing

Neonatal pigs were subjected to 2.5 × 2.5 cm full-thickness wounds. Wound size was periodically assessed throughout the healing process. Wound sites were collected for detailed histological analysis at 28, 43, and 58 days post-wounding (dpw) to track healing progression.

BrdU Labeling

To evaluate cell proliferation, neonatal pigs received intraperitoneal injections of 50 mg/kg of BrdU daily from P5 to P7. Tissues were subsequently collected at P8, P12, and P16 for comprehensive histological analysis.

Immunofluorescence Analysis

For immunofluorescence, cryo-preserved tissues were sectioned at 60 μm or 10 μm, and paraffin-embedded tissues at 10 μm. Standard immunofluorescence protocols were carefully followed, including necessary antigen retrieval for paraffin sections.

A comprehensive panel of primary antibodies targeting specific proteins such as ITGA6, LEF1, αSMA, PDGFRA, KRT10, MKI67, BrdU, SMAD1/5, PECAM1, and PDGFC was utilized.

Secondary antibodies included various Alexa Fluor conjugates, and DAPI was employed for nuclear counterstaining. Imaging was primarily conducted using Leica SP5/SP8 confocal microscopes, complemented by specialized imaging on Leica DMI8 fluorescence and Olympus FV3000 confocal microscopes.

Image Analysis and Quantification

Quantifications were rigorously performed using Fiji ImageJ (v.1.53c) and the ggplot package (v.3.4.0) in R (v.4.2.2). Key metrics quantified included epidermal thickness, rete ridge density, apical ridge length, hair density, scar size, and MKI67+/BrdU+ cell counts within different epidermal layers. Correlations between hair density and epidermal measurements were computed using linear regression.

Single-Cell RNA Sequencing (scRNA-seq)

Single-cell suspensions were meticulously generated from pig skin (E90, P3, P10, and 6 mo) through enzymatic digestion involving elastase, hyaluronidase, and collagenase IV. Libraries were prepared using the 10x Genomics scRNA-seq 3′ V3 Kit and sequenced on an Illumina NovaSeq PE150.

Data processing involved 10x Genomics Cell Ranger for alignment to the Sscrofa.11.1 genome. Subsequent analysis was performed with the Seurat package in R, encompassing quality control, normalization (SCTransform), dimensional reduction (UMAP), clustering (SLM algorithm), and cell type annotation based on canonical markers (e.g., keratinocytes, fibroblasts, pericytes, vascular cells, sweat gland cells). Pseudotime analysis was performed using Monocle3. Previously published human and mouse scRNA-seq datasets were also reanalyzed for comparative purposes.

Stereo-seq Analysis

For Stereo-seq analysis, PFA-fixed frozen cryo skin samples from P3, P10, and 6 mo pigs were sectioned at 10 μm. The Complete Genomics T FF v.1.2 kit was used, followed by DNBSEQ-T7 sequencing. Data processing utilized SAW (count, realign) for gene expression matrix generation and alignment.

Analysis was conducted using Stereopy in Python for quality control, normalization (sctransform), clustering (Leiden algorithm), and spatial cell type assignment based on canonical markers and observed spatial localization.

Cell-Cell Communication Analyses

CellChat and Spatial CellChat were employed to infer pathway and ligand–receptor interactions from both scRNA-seq and Stereo-seq datasets, respectively, leveraging the human ligand–receptor database. Analyses specifically focused on core basal and dividing keratinocyte, papillary fibroblast, pericyte, and blood vessel clusters.

Spatial CellChat was particularly valuable as it constrained interactions to biologically realistic distances, distinguishing between secreted and contact-dependent signaling.

Outgoing and incoming communication scores were meticulously calculated and visualized to elucidate intricate cellular crosstalk.

Statistical Analysis

Statistical analyses were conducted using R (v.4.2.2). Methods included one-way analysis of variance (ANOVA) with post hoc Tukey’s HSD, Welch’s two-sample t-test, and linear regression. A P-value of < 0.05 was consistently considered statistically significant. Critically, no data points were excluded from the statistical analyses.