Fig 1.
Number of differentially expressed genes during adipogenic and osteogenic differentiation in BMSC and ASC.
Upper panels denote number of differentially expressed genes (DEG; FDR ≤ 0.05 and P-value between comparison ≤ 0.05) in all time points during differentiation compared to time 0 (i.e., prior differentiation) without fold-change cut-off (top panels) or with 2-fold change cut-off (lower panels). Lower panels denote the number of DEG between consecutive time points with or without 2-fold change cut-off.
Fig 2.
KEGG pathways: overall dynamic adaptation of the main categories and sub-categories of pathways.
Overall impact and direction of the impact for the main KEGG pathway categories (red font) and sub-categories (black font) as calculated by the Dynamic Impact Approach. Reported are the “Impact”, i.e. the numerical effect or impact on the pathway, and the “Direction of the impact”, i.e. the overall estimated effect on the pathway (red = activated, i.e. the category or sub-category of pathways is estimated to be overall induced; green = inhibited, i.e. the category or sub-category of pathways is estimated to be overall reduced).
Fig 3.
KEGG pathways related to metabolism.
Shown are the direction of the impact of the most impacted metabolic-related pathways in each time point relative to pre-differentiation of adipogenic or osteogenic differentiation in ASC and BMSC. Blue font denotes carbohydrate metabolism-related pathways; dark red font denotes lipid metabolism-related pathways; purple font denotes amino acid metabolism-related pathways; green font denotes other amino acid metabolism-related pathways; dark yellow font denotes translation-related pathways; black font denotes cofactors and vitamins metabolism-related pathways (see details for all pathways in S2 File, sheet ‘KEGG Pathways’).
Fig 4.
KEGG pathways related to other categories.
Shown are the direction of the impact of the most impacted non metabolic-related pathways in each time point relative to pre-differentiation of adipogenic or osteogenic differentiation in ASC and BMSC. Blue font denotes signal transduction-related pathways; dark red font denotes signaling molecules and interaction-related pathways; dark purple font denotes transport and catabolism-related pathways; dark blue font denotes cell motility; purple font denotes Cell growth and death-related pathways; green font denotes cell communication-related pathways; dark yellow font denotes endocrine system-related pathways; red font denotes cancers-related pathways; black font denotes immune system diseases-related pathways (see details for all pathways in S2 File, sheet ‘KEGG Pathways’).
Fig 5.
Gene ontology biological process terms.
Direction of the impact of GO Biological process terms with the largest difference in the overall direction of the impact in adipogenesis compared to osteogenesis as calculated by the Dynamic Impact Approach. The two upper rows of figures report the terms with the largest overall direction of the impact in adipogenesis compared to osteogenesis. The last two rows of figures report the terms with the largest overall direction of the impact in osteogenesis compared to adipogenesis. The full results are available in S3 File.
Fig 6.
Relevant up-stream transcription regulators.
Most activated or inhibited up-stream transcription regulators (transcription factors and ligand-activated nuclear receptors) as estimated by the z-score for each comparison from Ingenuity Pathway Analysis. Red denotes predicted activation and green predicted inhibition. The complete results, including other types of up-stream regulators are available in S6 File.
Fig 7.
The left panel reports the heat map and the right panel the expression graphs of the κ-mean clustering analysis using Genesis [98] among the 2,200 DEG due to differentiation × time × cell type. In the expression graphs are reported the number of genes and the most enriched functions (Benjamini-Hochberg FDR < 0.05) as determined by DAVID [68]. The ‘Functional Annotation Chart’ and the ‘Functional Annotation Clustering’ results that summarize the complete results of the enrichment analysis performed using DAVID of genes in clusters are available in S7 File and S8 File. Cluster 10, 12, and 14 had not biological terms enriched with a FDR<0.05. The purple line in each graph denotes the mean pattern. The Y-axis of the graphs denote the log2 fold change in each time point relative to pre-differentiation or 0dd and the numbers in X-axis denote the day of differentiation (0, 2, 7, and 21 day) in each cell type (ASC = adipose-derived stem cells; BMSC = bone marrow-derived stem cells) during adipogenic or osteogenic differentiation.
Table 1.
Transcription factors controlling the expression of genes in clusters.
Reported are the 31 transcription factors with a p-value of overlap <0.0005. The p-value of overlap indicates the statistical significance of genes in the dataset that are downstream of the transcription factor. Complete results are available in S10 File.
Fig 8.
Overall functional adaptation of porcine ASC and BMSC during adipogenic and osteogenic differentiation.
The model encompasses the most impacted and enriched terms plus transcription factors inferred by the analysis of transcriptomics changes in ASC and BMSC during adipogenic and osteogenic differentiation. The red font denotes induction while green font denotes inhibition. Shapes of the terms indicate an increase or decrease of the function from pre-differentiation (time 0) to 21 days of differentiation (from right to left). The analysis suggested that ASC during adipogenic differentiation (panel A) had a large transcriptomics change (↰ (red arrow) genes whose transcription was increased; ↰ (green arrow) genes whose transcription was decreased; larger the size larger the number) with a more pronounce number of down-regulated compared to up-regulated genes. On the right, before the arrows, are reported the symbol of the most important transcription factors (TF) apparently regulating the genes affected by differentiations in each cell types. Red font TF are estimated to be activated and green are estimated to be inhibited. Shape of the TF denote change in activation (if larger in red from right to left → more activated during differentiation; if larger in green from right to left → more inhibited during differentiation; shape are derived from data reported in Fig 6). The functional analysis suggested an overall large induction of metabolism, encompassing triacylglycerol (TAG) synthesis with a fundamental role of unsaturation of long-chain fatty acids (LCFA) and import of glycerol. The amino acid (AA) metabolism, the metabolism of nicotinate and nicotinamide metabolism and pantothenate and CoA biosynthesis were induced with likely production of metabolites capable of direct or indirect positive effect on adipogenesis, partly through PPARγ. The ECM signaling, xenobiotics metabolism, and peroxisome were strongly induced. A potential increase in tumorigenesis by adipogenic differentiation can be deduced by the data. The cell proliferation and the cell-to-cell interactions were evidently inhibited by adipogenic differentiation. The transcriptomics data indicated also a large inhibition of immunogenicity as differentiation progressed in ASC. Functional analysis of transcriptomics changes by adipogenic differentiation in BMSC (panel B) suggested a very similar effect as for ASC. The osteogenic differentiation in ASC (panel C) and BMSC (panel D) was characterized by an increase in overall metabolism (larger in ASC vs. BMSC) but with an overall decrease of steroid biosynthesis and protein synthesis machinery. Data also indicated an overall increase in cell adhesion and accumulation of ECM with components such as collagen, and an increase in VEGF production with a likely consequent intensification of angiogenesis (if in an in vivo setting). Amid transcription factors the data suggested a pivotal role of PPAR isotypes and other transcription factors known to be involved in regulating lipid metabolism in controlling adipogenesis and novel TF in regulating osteogenesis. As for the adipogenic differentiation, also for the osteogenesis the data suggested that ASC were characterized by a decreased immunogenicity and an intensification of mineralization by the augmented expression of ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) that plays a pivotal role in the nicotinate and nicotinamide metabolism and pantothenate and CoA biosynthesis.