Edge attributes. Node attributes

Transcription

1 HMDB ID input pane Network view Node attributes Edge attributes Supplemental Figure 1. Cytoscape App MetBridge Generator. The left pane is Cytoscape App MetBridge Generator (code name: rsmetabppi). User can input HMDB numbers to search for subnetwork involving the given metabolites. Upper-right pane shows MetBridge network. Red, blue and pink nodes represent metabolites, enzymes, and bridge proteins, respectively. Pink, red and blue edges represent metabolism, manually curated metabolism and PPI respectively. Selected nodes and edges are colored in yellow and red, respectively, and also marked by the red arrow. The detailed information on the selected nodes (node attributes) is displayed in the lower pane. The detail on the selected edges (edge attributes) is displayed in the lower part of the figure. DKD

2 A B catabolic metabolic lipid catabolic small molecule catabolic cellular catabolic biological_ intracellular sarcomere myofibril cellular small molecule metabolic nitrogen compound metabolic cellular lipid catabolic primary metabolic cellular metabolic lipid metabolic cellular nitrogen compound lipid oxidation metabolic lipid modification cellular amino acid and derivative amine metabolic metabolic organic acid metabolic fatty acid oxidation cellular lipid metabolic cellular ketone metabolic cellular amine metabolic cell cell part cellular_component intracellular part membrane-bounded intracellular intracellular part contractile fiber part cytoplasm contractile fiber intracellular membrane-bounded cytoplasmic part microbody peroxisome organic acid catabolic fatty acid catabolic oxoacid metabolic membrane-enclosed lumen intracellular part mitochondrion fatty acid beta-oxidation amine catabolic cellular amino acid metabolic fatty acid beta-oxidation using acyl-coa oxidase carboxylic acid catabolic carboxylic acid metabolic cellular amino acid catabolic macromolecular complex lumen mitochondrial lumen mitochondrial part fatty acid alpha-oxidation fatty acid metabolic branched chain family amino acid catabolic intracellular lumen protein complex mitochondrial matrix monocarboxylic acid metabolic branched chain family amino acid metabolic citrate metabolic fatty acid beta-oxidation multienzyme complex interphase C modification-dependent protein catabolic proteolysis involved in cellular protein catabolic ubiquitin-dependent protein catabolic modification-dependent macromolecule catabolic cellular protein catabolic protein catabolic protein modification cellular protein metabolic cellular macromolecule catabolic protein metabolic macromolecule catabolic macromolecule modification cellular component movement cellular macromolecule metabolic cell cycle phasecell cycle macromolecule metabolic cellular catabolic organization transmembrane receptor protein tyrosine kinase enzyme linked receptor protein cell surface receptor linked catabolic primary metabolic proteolysis signaling regulation of hydrolase activity post-translational protein modification regulation of catalytic activity protein ubiquitination protein modification by small protein conjugation or removal regulation of biological regulation of apoptosis regulation of endopeptidase activity protein modification by small protein conjugation positive regulation of biological regulation of caspase activity Enzymes pore complex keratin filament protein complex membrane intrinsic to membrane integral to membrane membrane part cullin-ring ubiquitin ligase intracellular complex ubiquitin ligase complex G1/S transition of mitotic cell cycle cellular metabolic positive regulation of cellular macromolecular complex metabolic intracellular part biological regulation microtubule intermediate filament cell cycle interphase of mitotic cell cycle regulation of cellular microtubule cytoskeleton cellular positive regulation of cell death cytoskeletal part mitotic cell cycle intracellular mitochondrion organization biological_ regulation of programmed cell death intermediate filament cytoskeleton intracellular regulation of molecular function regulation of cell death epidermal growth factor receptor cellular component organization cytoskeleton D 5.00E-2 p-value cell part cellular_component intracellular membrane-bounded < 5.00E-7 cell membrane-bounded intracellular part cytoplasm part cytoplasmic part mitochondrial part mitochondrion envelope membrane-enclosed lumen envelope envelope lumen mitochondrial intermembrane space mitochondrial envelope regulation of peptidase activity Bridge proteins Supplemental Figure 2. GO terms enriched in enzymes and bridge proteins in the network connecting thirteen metabolites. Each node represents GO term. Each arrow represents hierarchical relationship between the terms. Significantly enriched terms in the hierarchy were colored depending on their significance. GO biological es and cellular components enriched in the enzymes (A and B, respectively) and those enriched in the bridge proteins (C and D, respectively) are shown.

3 Control MDM2 db/m db/db Supplemental Figure 3: Representative image of immunohistochemistry of MDM2 in kidney tissue of db/m and db/db mice. There were no clear differences in the tissue expression level of MDM2 between db/m and db/db mice. n = 3 per group. Magnification: 40x.

4 A Nephrin B Podocalyxin Plac Nut Plac Nut C Podocin D CD2AP Plac Nut Plac Nut E Synaptopodin F WT Plac Nut Plac Nut Supplemental Figure 4. Expression analyses of marker genes for diabetic nephropathy. Podocyte marker gene expression levels for control mice treated with placebo (Plac) and Nutlin-3a-treated diabetic mice (Nut) are shown in A-F. Benjamini-Hochberg corrected p-values were below 0.05 for all the genes.

5 MCCC2 Glomeruli Tubules log 2 (mrna intensity) p = p = log 2 (mrna intensity) p = p = LD ERCB Pima LD ERCB Pima Supplemental Figure 5: Expression analyses of methylcrotonoyl-coa carboxylase 2 (MCCC2) in tissue biopsy of human kidney. Gene expression levels of MCCC2 in glomeruli and tubules of living donors (LD) were compared with those of ERCB and Native Americans (Pima).

6 Supplemental methods Assessment of hub bridge proteins We attempted to extract bridge proteins which have significant number of interactions to the enzymes regulating our thirteen metabolites based on a simple statistical framework. First, we classified the set of KEGG enzymes in our MetBridge network (Z) into (A 1 ) those which are associated with at least one of given set of metabolites m M (M is the set of our thirteen metabolites in this case) or (A 2 ) those which are not associated with any one of m M (z A 1 z A 2, A 1 A 2 ={ } ). The enzymes which directly interact with those which are associated with one of our thirteen metabolites were also classified as A 1 in order to account the possibility that such interactions among a pair of enzymes may constitute an enzymatic complex or a functional unit of the metabolic reaction. We searched for bridge proteins (P) which interact with at least one enzyme in A 1. Then for each protein p P, we classified enzymes z Z into (B 1 (p)) those which interact with the protein and (B 2 (p)) those which do not (z B 1 (p) z B 2 (p), B 1 (p) B 2 (p) = { }). Thus, each enzyme z Z can be classified as A 1 or A 2, and also B 1 (p) or B 2 (p) for a given protein p. Subsequently we tested enrichment of enzymes which are categorized both in A 1 and B 1 (p) using hypergeometric test; Let r A1 and r B1 (p) be the actual

7 probability of z classified as A 1 and B 1 (p) respectively. Let r A1B1 (p) be the actual rate of z classified as both A 1 and B 1 (p). Then, the hypotheses to test are H 0 : r A1B1 (p) = r A1 r B1 (p) and H 1 : r A1B1 (p) > r A1 r B1 (p), where r A1, r B1 (p) and r A1B1 (p) are estimated by r A1 = A 1, Z r B1(p) = B 1(p) Z and r A1B1(p) = A 1 B 1 (p) Z respectively. This was to test whether a given bridge candidate protein has significantly more interactions to the enzymes regulating our thirteen metabolites compared to other KEGG enzymes. The number of calculated p-values were identical to the number of bridge proteins. These p-values were corrected using Benjamini Hochberg procedure. Calculating expected number of PPIs among MetBridge DKD network The whole MetBridge network contained edges among proteins. Thus, under the assumption that two different proteins randomly picked from MetBridge interact at probability p, the estimated probability p indicating an interaction between randomly picked two proteins was 58703/ ( ) We tested whether the probability p 13 of two proteins randomly picked from MetBridge DKD is equal to p (H 0 : p 13 = p, H 1 : p 13 > p). Since MetBridge DKD contained 291 proteins, the expected number of edges were calculated to be ( 291 ) 58703/ ( )