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Ryan et al. J Transl Genet Genom. 2025;9:48-61 https://dx.doi.org/10.20517/jtgg.2024.87 Page 50

MATERIALS AND METHODS
Derivation and differentiation of iPSC-derived podocytes
iPSCs were derived from dermal fibroblasts collected via a punch biopsy from a male FD patient carrying
the p.Met284Thr GLA variant and who presented with renal and cardiovascular disease, as previously
described . Two age-matched control lines were also reprogrammed following informed consent.
[10]
Podocyte differentiation followed Wise et al.’s protocol [10,16] , using DMEM/F12 with FBS, NEAA, penicillin-
streptomycin, activin A, bone morphogenetic protein 7 (BMP7), retinoic acid, β-mercaptoethanol and Y-
27632 (ROCK inhibitor) for enhanced attachment. Media changes occurred every other day for 10 days,
with activin A, BMP7, and retinoic acid removed for long-term culture.

Transmission electron microscopy
Differentiated podocytes were isolated and fixed in Karnovsky’s fixative and washed in 1 mL 0.1 M
cacodylate buffer before post-fixation in 1% osmium tetroxide for one hour at room temperature. Serial
dehydration was performed before embedding in resin. Pellets were thin-sectioned with an ultra-microtome
and placed in copper orthogonal grids before staining with 4% uranyl acetate. All sections were imaged
using a Hitachi H7500 transmission electron microscopy (TEM) (Hitachi) or Tecnai T12 TEM (FEI) with
Gatan Microscopy Suite Software (Gatan Incorporated). Image J was used to quantify the percentage of
lysosomal area per field and lysosome size in control and FD podocytes taken at ×10,000 magnification.

Proteomic analysis and enrichment studies
Proteomic data were analyzed to identify key differences between FD and control iPSC-derived podocytes.
Proteomic analysis was performed with liquid chromatography and tandem mass spectrometry (LC-MS/
MS) on FD iPSC-derived podocytes or two pooled control lines using triplicate pellets via label-free
[10]
quantification (LFQ) as previously detailed . Sample preparation involved solubilization in SDS buffer,
sonication for DNA shearing, and clarification via centrifugation. Protein quantification was carried out
using the BCA Protein Assay, followed by digestion with trypsin using S-Traps. Peptides were purified by
solid-phase extraction and analyzed using a Dionex UltiMate 3000 system coupled to an Orbitrap Eclipse
Tribrid mass spectrometer. Separation occurred on C18 columns under optimized acetonitrile gradients,
with ionization performed via nanoelectrospray and FAIMS for gas-phase separation.

Data were acquired in a data-dependent mode, with high-resolution scans for both precursor ions and
fragments, employing FAIMS compensation voltages. Processing of raw data was performed using Fragpipe,
with protein quantification by LFQ match-between-runs (LFQ-MBR) and searches against the SwissProt
human proteome. LFQ-Analyst was used for differential protein analysis, applying limma for statistical
modeling, with cut-offs set at an adjusted P-value < 0.05 and log2 fold-change > 1.

Proteomic data analysis and visualization
Principal component analysis (PCA) was conducted to visualize variance between samples. Hierarchical
clustering for heatmap generation was performed using the ComplexHeatmap package in R, as previously
reported . Differentially expressed proteins were selected based on a log2 fold change > 1 and an adjusted
[10]
P-value < 0.05. Enrichment analysis using gene ontology (GO) and Kyoto Encyclopedia of genes and
genomes databases (KEGG) provided biological insights, with results visualized using bar and line charts for
enriched pathways. GO enrichment analysis was conducted to identify overrepresented biological processes,
molecular functions, and cellular components among differentially expressed proteins. Enriched terms were
visualized as bubble plots, with bubble size indicating gene count and the X-axis indicating the level of
statistical significance. A smaller -log10 (adjusted P value) indicates greater statistical significance
(P-value < 0.05). Volcano plots were created using LFQ-Analyst to visualize differential protein abundance,
plotting log2 fold change against the negative log10 of the adjusted P-value. Proteins with significant up- or
downregulation were highlighted. A full protocol, including details on peptide purification,