To gain the insight on the mitochondrial OXPHOS activity among cHCEC SPs, proteomics by LC/MS were performed. The cell lysates of cHCECs at passage four were used. The proteome analysis for 4641 proteins in total were performed, as recently described in detail.
9,27 The analysis for the enzymes involved in the TCA cycle and pyruvate metabolism is firstly presented here. The high-quality cHCECs containing the CD44
−/+ mature differentiated cHCEC SPs at a ratio of 93.9% (effector ratio = E-ratio,
n = 3) and the low-quality cHCECs containing the CST-CD44
++/+++ immature cHCEC SPs at a ratio of 73.8% (
n = 3) were analyzed. The procedures for the preparation of these two SPs and the proteome analysis were recently detailed (
Supplementary Fig. S1).
9,27 Lysates from three aliquots of each high-quality or low-quality cHCEC were provided for the analysi
s. Peptides were analyzed using an LTQ-Orbitrap-Velos mass spectrometer (Thermo Fisher Scientific, Inc., Waltham, MA) combined with an Ulti-Mate 3000 RSLC nano-flow HPLC system (Thermo Fisher Scientific, Inc.). Protein identification and quantification analysis were performed with MaxQuant software. The MS/MS spectra were searched against the
Homo sapiens protein database in Swiss-Prot, with a false discovery rate set to 1% for both peptide and protein identification filters. Only “Razor1unique peptides” were used for the calculation of relative protein concentration. The LC/MS data set, composed of 4641 proteins in total, was obtained by use of Proteome Discoverer 2.2 software. After removal of the data in which the abundance ratio could not be calculated, we analyzed the remaining data by means of a web-based program, DAVID v6.8 (The Database for Annotation, Visualization and Integrated Discovery;
https: //david.ncifcrf.gov). Finally, it ended up with 4315 genes, each with a unique DAVID Gene ID, for the subsequent analyses. Further investigations for the focused genes were performed by using DAVID and its options “BIOCARTA” and “KEGG_PATHWAY.” We referred their original databases of BioCarta (
https://cgap.nci.nih.gov/Pathways/BioCarta_Pathways) or KEGG (Kyoto Encyclopedia of Genes and Genomes;
https://www.genome.jp/kegg/) and showed the referred genes/pathways in the figures with slight modifications. For the clarity of the procedures, the details of the procedures were cited here from the reference 5 as
Supplementary Fig. S2, together with the detailed legend.