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Additional file 6 Fig. S6. Methylation status of CpG associated with annotated enhancers. Related to Fig. 7. Significant differentially methylated probes were annotated with the 450k_Enhancer feature and the proportion of probes attributed to each feature counted. Arrows indicate increased hypomethylation and reduced hypermethylation of enhancers in the TM/DM comparison.

Additional file 2 Fig. S2. PGRMC1 phosphorylation mutants do not affect AG-205-induced death. Related to Fig. 2. (A) AG-205-induced cell death is unaffected by PGRMC1 phosphorylation status. Cells were incubated in the presence of the indicated AG-205 concentrations (n = 8: 3x line 1, 3x line 2, 2 x line 3) or DMSO vehicle control (n = 3: 1x each cell line), and percentage viable cells was calculated relative to untreated cell controls (n = 9: 3 replicates per cell line) using MTT assay. (B) AUC results for values from A greater than 25 μM reveal no significant differences in response to AG-205 treatment between cell lines (p > 0.85, post-hoc Bonferroni after 1 way ANOVA for AG-205 treatment). The apparently greater survival of DM cells at 25 μM AG-205 observed in this panel was never observed in multiple other repeat experiments.

Additional file 5 Fig. S5. Methylation status of CpG associated with annotated coding genes. Related to Fig. 7. Significant differentially methylated probes were annotated with the UCSC gene feature and the proportion of probes attributed to each feature counted. The y-axis shows the frequency of hypermethylated-hypomethylated probes per feature, and the x-axis shows the difference in those frequencies between WT/MP, DM/WT and TM/DM. 3’UTR: 3′ untranslated region; 5’UTR: 5′ untranslated region; Body: Between the ATG and stop codon; irrespective of the presence of introns, exons, TSS, or promoters; ExonBnd: exon boundaries: TSS1500/TSS200: within indicated number of residues of transcription start site (TSS).

Additional file 1 Fig. S1. Representative hyperspectral autofluorescence cell images from the measurements. Related to Fig. 1. (A) Mean cellular intensity of hyperspectral autofluorescence channel 18 [495 nm(Ex), 700 nm(Em)], which may reflect porphyrin or protein-bound red-shifted flavin emission [46], is significantly affected by PGRMC1-HA phosphorylation status. The table provides Kolmogorov-Smirnov test p values from pair wise comparisons. (B) The ratio of hyperspectral autofluorescence channels 3 [375 nm(Ex), 450 nm(Em)] to channel 12 [435 nm(Ex), 587 nm(Em)] differs significantly between cells. The table follows C. (C) Individual channels #3 and #4 from (B) as listed in Table S1 (left) and the same two channels superimposed (right).

Additional file 1:Figure S1. Detailed views of selected pathways identified by WebGestalt analyses. Related to Fig. 3. All panels are adapted from File S6. Heat map colors follow Fig. 3. (A) Principal component (PC) analysis of SWATH-MS proteomics results showing distribution of PC1 and PC2. PC1 corresponded to pathways associated with ribosomes and translation, while PC2 corresponded to pathways associated with mRNA splicing processing (see File S3). (B) Proteins associated with PI3K/AKT activity (WebGestalt Database: PC, DB_ID:1648, “Class I PI3K signaling events mediated by AKT”) are less abundant in TM cells. (C) F1/F0 ATPase subunits elevated in WT and TM cells. (D) Abundances of proteins associated with protein folding and microtubule function are altered by PGRMC1 phosphorylation status. Proteins detected in any of the following WebGestalt pathways or functions (1–4) or a manual search (5) are mapped against their expression profiles. 1) cellular component chaperonin-containing T-complex GO:0005832. 2) PC pathway Chaperonin-mediated protein folding DB_ID:710. 3) cellular component microtubule GO:0005874. 4) PC pathway Protein folding DB_ID:712. 5) Description from the list of 243 proteins (File S6) contains keywords “tubulin” or “microtubule” (manual search) (Adapted from File S6). 2-tailed t-test p-values for all sample comparisons are available in File S4. (E) Proteins associated with nuclear import/export that are elevated in DM cells. (F) Antigen processing and presentation enzymes are affected by PGRMC1 phosphorylation status. Manual additions to KEGG pathway ID:04612 “Antigen processing and presentation" (no yellow shading: from File S6 and File S5) are indicated with yellow highlighting. Figure S2. Highest and lowest differentially abundant proteins. Panels show the six most (+) and least (−) abundant proteins for each cell type that were significantly differentially abundant between cell types. Related to Fig. 3. Identical colored symbols depict the same protein in different cell types, where circles represent high abundance and triangles represent low abundance. E.g. Mitochondrial import receptor subunit TOM40 (O96008), CDP-diacylglycerol-inositol 3-phosphatidyltransferase (CDIPT, O14735) (phosphatidylinositol synthesis) and transcriptional coactivator PSIP1 (O75475) are more abundant in WT and TM. Aldehyde dehydrogenase 1A3 (P47895), APOC3 (P02656) and APOA1 (P02647) are less abundant in DM and TM, whereas the receptor tyrosine kinase ephrin type-A receptor 2 (EPHA2, P29317) is among the lowest abundance differential proteins in WT and TM. Protein abundances (measured ion intensities) for all proteins are available in File S2. Figure S3. Proteins associated with predicted Estrogen Receptor Related 1 (ERR1) transcription factor activity are more abundant in WT and TM cells. Related to Fig. 3 and File S6. Data are available via ProteomeXchange with identifier PXD014789. (A) Proteins quantified by SWATH-MS and predicted by WebGestalt Transcription Factor target enrichment analysis (WebGestalt Database: Transcription Target, Name: hsa_TGACCTY_V$ERR1_Q2, ID:DB_ID:2414) to be dependent upon ERR1 transcription (Adapted from File S6). Heat map colors follow Fig. 3. (B) Western blot of shRNA attenuation of ERR1 (top panel) in WT cells, compared to scramble shRNA control. Lower panel: beta actin loading control. (C) ERR1 attenuation by shRNA induces morphological changes to WT cells. (D) Ratio of rounded to other cells as scored for replicate images from each of the cell lines from B. p 10 fluorescent intensity units to the right of the reference line in (A). n = 6 for each cell type, being 6 replicates of MP cells, or duplicate measurements of each of 3 independent lines 1–3 (n = 3 × 2 = 6) for WT, DM and TM cells. White arrows indicate the same differences as in (A). There was significant difference between the means (Kruskal-Wallis Test p

Additional file 8 Table S1. Spectral channel filters employed for hyperspectral autofluorescence imaging. Related to Fig. 1. For further details of this approach see Gosnell et al. [44].

Additional file 8 Table S1. Spectral channel filters employed for hyperspectral autofluorescence imaging. Related to Fig. 1. For further details of this approach see Gosnell et al. [44].

Additional file 3 Fig. S3. SWATH-MS proteomic quantification of Nicotinamide phosphoribosyltransferase. Related to Fig. 6. The figure shows the abundance profile of P43490 nicotinamide phosphoribosyltransferase (NAMPT) from the SWATH-MS proteomics quantification of the accompanying manuscript [10].

Additional file 10 Table S3. Unique KEGG pathways detected for TM/DM hyper and hypo-methylated gene sets. Related to Fig. 7. The identities of the 11 hypermethylated and 7 hypomethylated pathways unique to the TM/DM comparison from Fig. S7B are given. Full results are available in File S1.

Additional file 9 Table S2. GO pathways enrichment results. Related to Fig. 7. The top ten GO enrichments for each cell comparison from Fig. 7. Full results are available in File S1.

Additional file 10 Table S3. Unique KEGG pathways detected for TM/DM hyper and hypo-methylated gene sets. Related to Fig. 7. The identities of the 11 hypermethylated and 7 hypomethylated pathways unique to the TM/DM comparison from Fig. S7B are given. Full results are available in File S1.

Additional file 9 Table S2. GO pathways enrichment results. Related to Fig. 7. The top ten GO enrichments for each cell comparison from Fig. 7. Full results are available in File S1.

Additional file 4 Fig. S4. PGRMC1 phosphorylation status affects the NNMT pathway. Related to Fig. 6. (A) Metabolomics quantification of S-adenosyl-Methionine (SAM) levels for the indicated cell lines, representing n = 12 (four technical replicates for each of three independent cell lines per PGRMC1 condition). (B) RT-PCR quantification of NNMT mRNA levels after treatment by an NNMT-specific shRNA (NN) or a random scramble shRNA control (scr) in TM cells stably expressing lentiplasmid-driven shRNAs. RT-PCR Methods follow A. p

Additional file 3 Fig. S3. SWATH-MS proteomic quantification of Nicotinamide phosphoribosyltransferase. Related to Fig. 6. The figure shows the abundance profile of P43490 nicotinamide phosphoribosyltransferase (NAMPT) from the SWATH-MS proteomics quantification of the accompanying manuscript [10].