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Supplementary Materials for

Interconnected Network Motifs Control Podocyte Morphology and Kidney Function

Evren U. Azeloglu, Simon V. Hardy, Narat John Eungdamrong, Yibang Chen, Gomathi Jayaraman, Peter Y. Chuang, Wei Fang, Huabao Xiong, Susana R. Neves, Mohit R. Jain,

Hong Li, Avi Ma’ayan, Ronald E. Gordon, John Cijiang He,* Ravi Iyengar*

*Corresponding author. E-mail: [email protected] (R.I.); [email protected] (J.C.H.)

Published 4 February 2014, Sci. Signal. 7, ra12 (2014) DOI: 10.1126/scisignal.2004621

Thes PDF file includes:

Methods Fig. S1. Results for enrichment analysis for down-regulated proteomic components in glomeruli from puromycin-induced nephropathy animals. Fig. S2. Enrichment analysis for the second proteomics experiment (biological replicate) with puromycin-induced nephropathy rats. Fig. S3. Protein-protein interaction network constructed with down-regulated components as seed nodes along with one intermediate. Fig. S4. Multimodal experimental constraints for the multicompartmental dynamic model of cAMP/PKA signaling network topology. Fig. S5. Analysis of CREB activity by EMSA to confirm CREB binding to DNA. Fig. S6. Process for building dynamic graphs and visual summary of the associated computational methods. Fig. S7. Dynamic graphs of individual component and motif activities. Fig. S8. Relative contribution of FFM paths and their lifetimes. Fig. S9. Spread of RT-PCR and morphometric data for animal studies. Fig. S10. High-magnification transmission electron microscopy (TEM) images showing in vivo actin bundles. Table S1. Proteins that were significantly up- or down-regulated according to differential proteomics of glomeruli from control (saline-injected) and puromycin-injected rats. Table S2. Abundance of different PKA subunits as measured by the two independent proteomic experiments. Table S3. Simulation parameters for the computational model. Table S4. Parameter normalized local sensitivity analysis.

Table S5. Abundance of glomerular and tubular markers as quantified by proteomic analysis. References (48–93)

SUPPLEMENTARY METHODS Electrophoretic Mobility Shift Assay (EMSA) The sequence for the double-stranded DNA that binds CREB was used for the synthesis of the following oligonucleotides 5’-TCAAATTGACGTCATGGTAA-3’ and 5’-TTACCATGACGTCAATTTGA-3’. DNA probes were prepared by annealing complementary single-stranded oligonucleotides with 5’GATC overhangs (Genosys Biotechnologies, Inc.) and labeled by filling in with [α-32P]dGTP and [α -32P]dCTP using Klenow enzyme. DNA-binding complexes were separated by electrophoresis on a 5% polyacrylamide-Tris/glycine-EDTA gel, which was dried and exposed to X-ray film. The specificity of DNA-protein binding was verified by incubation with 100-fold excess of cold probe and by super-shifted with specific anti-CREB antibody (Cell Signaling Technology). All experiments were repeated at least 3 times and representative experiments are shown here. MAPK 1,2 Kinase Enzyme Activity Assay This assay was done in two parts: immunoprecipitation of MAPK1,2 and determination of MAPK1,2 activity using a radio-assay kit (Upstate MAP Kinase/ Erk Assay). Briefly, podocytes lysates were immunoprecipitated by incubating with 4 µg of anti-MAPK1,2 antibody (Cell Signaling) at room temperature for 1hr, followed by further incubation at 4oC with 60 ml of protein A/G plus agarose beads (Santa Cruz, CA) for overnight. Immunoprecipites (50µg) were incubated with 15 mM MgCl2, 1.00mM ATP, γ-P32 ATP (10000 to 16000 CPM), 4mM MOPS pH7.2, 5mM b-glycerol phosphate, 1mM EGTA, 0.2mM sodium orthovanadate, 0.2mM dithiothreitol with 4mM PKC inhibitor (catalog # 12-121), 0.5M PKA inhibitor (PKI) (catalog # 12-151), and 4mM compound R24571. After incubation for 10 minutes, the reaction was stopped and 25ml of reaction mixture were pipetted slowly onto the center of a P81 phosphocellulose papers. After washing with 0.75% phosphoric acid in water and 0.75% phosphoric acid in ethanol, the papers were dried and counted in 5ml of scintillation biodegradable cocktail EcoLife (ICN Biomedicals) using a scintillation counter (Beckman LS6500). Experiments were done in triplicates and each experiment was repeated for at least 3 times. MAP kinase activities were normalized by total immunoprecipited MAPK1,2, as determined by densitometric analysis of bands in Western blot. Evaluation of Glomerular Purity In order to ensure purity, glomeruli, which were isolated in 4ºC immediately following the sacrifice of the animal, were inspected under low power light microscopy for tubular contamination. Accordingly, no large pieces of proximal tubules were visible. We further analyzed proteomic spectral abundance (48) for the 15 well-known glomerular proteins comparing them against 10 well-known tubular proteins. The results of protein abundance analysis are presented in table S5 below. Dynamic Graphs

Dynamic graphs were built from the compartmental ODE model developed with Virtual Cell. A Petri net representation of the model was created with the SBML conversion feature of the software Snoopy (49). First, the results of a p-invariant analysis were used to create an interaction graph of the model. Then, the results of a t-invariant analysis on every p-invariant subnets were used to create an influence graph of the model [for more information on Petri net theory and related analysis methods, see David and Alla (50)]. In parallel, the numerical data from the simulation of the mathematical model in Virtual Cell was used to compute activation and reaction flow values to assign color intensities to the nodes and edges of the influence graph. The result is one intensity graph with shaded nodes and edges for each simulation time step (fig S6). Assembled together , these graphs of changing shades form a dynamic graph and

can be visualized as a movie (fig. S7). Such a movie is akin to a cartoon movie in which each frame is shown as a fixed temporal sequence. Because, here frames arise from ODE simulation, the dynamics show the rate of change of reaction and state of the component. The nodes are assigned different shading (or coloration) to represent a, the percentage of activation

of the signaling component out of the total concentration. The value is the

ratio of the sum of all active states of a given signaling component (e.g. multiple subunits) over the total concentration of this component. Except for cAMP, MKP1, and MKP1 mRNA, the total concentration of signaling components is constant over time. The edges are assigned grayscale shades to represent r, the percentage of reaction flow of an interaction out of the maximal value.

The value is a measure of the relative reaction flow value using the

maximum attained during the simulation as the denominator. For the incoming edges on the nodes MEK, PKAn, MAPKc, and CREB, the same denominator was used for all edges to allow for visual comparison. Also, the maxima from the simulations with the Isoproterenol-dependent activation were used to generate the dynamic graphs of the two other simulations. See fig. S6 for a visual summary of the method for building a dynamic graph, and Hardy and Iyengar (51) for more information. Computational Assessment of Motif Lifetime The lifetime of a FFM is the period during which the output of the motif is above the threshold that will cause an arbitrary level of activation of the ultimate output of the signaling pathway. In this study, we used a 33% level of CREB activation. Thresholds for regulatory motifs activation are determined from the values of the downstream signal amplification. The signal amplification A of one enzymatic reaction, for example ** YY X⎯→⎯ where Y is phosphorylated by X* and

YY P⎯→⎯* where Y* is dephosphorylated by P, corresponds to the following equation:

*]/[*]/[

YJXJA

YP

XYXY = , where J is the reaction flow of this reaction. An amplification value greater

than 1 means that the signal is amplified at that step. The product of all amplifications between the source and the output of a linear signaling cascade is the signal amplification value of this path. If the path comprises a coherent OR FFM in which the two paths of the FFM activate the target, then the summation of the amplification values from the two paths is used. As we defined it, the signal amplification value is a linear simplification of nonlinear reactions, thus it is time-dependent. This measure of motif activity, as opposed to individual component activity, is based on the work of Heinrich et al. (52). For example, the FFM1 is deemed active when the product of the output of the motif [Raf*] and the signal amplification value of the downstream path up to CREB is equal or above 33% of the maximum concentration of active CREB. The start of the lifetime bars is the time point when this product is above the threshold and the end is when it goes below. Simply put, a FFM is defined as active when its downstream target reaches an activity level above a defined threshold.

ionconcentrat total

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Supplementary Figure S1

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MP0009643_abnormal_urine_homeostasis_

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mitochondrion (GO:0005739)

cell projection membrane (GO:0031253)

mitochondrial intermembrane space (GO:0005758)

basolateral plasma membrane (GO:0016323)

mitochondrial part (GO:0044429)

cytosol (GO:0005829)

cell surface (GO:0009986)

membrane raft (GO:0045121)

mitochondrial matrix (GO:0005759)

actin cytoskeleton (GO:0015629)

kidney

liver

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Appendix

Figure S1. Results for enrichment analysis for down regulated proteomic components in glom-eruli from puromycin-induced nephropathy animals. Green arrows point to concepts pertinent to differentiation of podocytes, which were significantly enriched (Fisher exact test with Bonferroni correc-tion). Bar size indicates normalized negative-log of p-values. Top enriched terms according to (A) Mouse Genome Informatics Mammalian Phenotype Ontology, (B) Gene Ontology, cellular component, (C) Mouse Gene Atlas, and (D) Human Gene Atlas.

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EGFR PRKACA

PKD1 CAMK2D CAMK2B CAMK2G

SRC CSNK1A1

PAK2 PRKCA

MAP2K2 OXSR1 PRKCD PIK3CB

BCR

-log(p-value)

Supplementary Figure S2A

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Kidney

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SubthalamicNucleus

Lung

Colorectaladenocarcinoma

colon

Liver

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Ovary

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Log2 Change: -0.6 0 0.6

Figure S2. Enrichment analysis for the second proteomics experiment (biological replicate) with puromycin-induced nephropathy rats. (A) List of top 15 upstream kinases with their negative-log p-values. (B) Protein abundance of podocyte differentiation markers, housekeeping markers, and de-differentiation markers. (C) Enrichment analysis for the highest ranked MGI ontology terms. (D) Enrichment analysis for the highest ranked Human Gene Atlas terms.

Supplementary Figure S3Figure S3. Protein-protein interaction network constructed with down-regulated components as seed nodes along with one intermediate. The 91 down-regulated proteins were used as seed nodes (red) along with single intermediate genes (green) from the X2K suite. The final network has 212 nodes and 948 edges. Enrichment analysis using this signaling network also ranked PKA as a significant upstream kinase (p < 0.001, Fisher exact test).


B)

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Figure S4. Multimodal experimental constraints for the multicompartmental dynamic model of cAMP/PKA signaling network topology. (A) Cultured podocytes were stimulated with 10 μM isoproter-enol under control conditions, with U0126, with Rp-cAMP, or when transfected with dominant-negative PKA (PKA-DN). The amount of active CREB* (Ser133 -phosphorylated CREB) was measured by immu-noblotting. (B) Time courses comparing numerical simulations and experiments of the relative amount of active CREB under various treatment conditions and model predictions (duplicate of Fig. 4). (C) Cells were treated with 100 μM of the cAMP GEF-selective agonist 8-pMeOPT-2'-O-Me-cAMP or 100 μM of the PKA-selective agonist 6-Bnz-cAMP. The amount of activated MAPK (MAPK*) was quantified by immu-noblotting. (D) Cells transfected with wild-type Rap1 (Rap1-WT) or dominant-negative Rap1 (Rap-DN) were stimulated with isoproterenol. The amount of activated MAPK was analyzed by immunoblotting. (E) Podocytes treated with Rp-cAMPs were stimulated with isoproterenol, and active MAPK and total MAPK were measured by immunoblotting. (F) Podocytes treated with Rp-cAMPs or U0126 were stimulated with isoproterenol, and the amount of MAPK activity for the whole cell was measured by radio enzyme activity assay. All quantified data are presented as mean ± SEM of at least 3 experiments.

Supplementary Figure S4 (continued)

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Supplementary Figure S5Figure S5. Analysis of CREB activity by EMSA to confirm CREB binding to DNA. The activities of CREB under various conditions were measured by electrophoretic mobility shift assay (EMSA) in the presence of MEK inhibition with U0126 or PKA inhibition with PKA-DN. After stimulation with 10 μM isoproternol for the indicated time interval, nuclear proteins were extracted. EMSA were performed with 105 cpm of labeled probe (CREB: 5’- CAAATTGACGTCATGGTAA -3’; 5’- TTACCATGACGTCAATTT-GA-3’) and 5 mg of nuclear extracts. The DNA binding complexes were separated on 5% polyacrylamide gel, and then exposed to X-ray film. The specificity of DNA-protein binding was verified by incubation with excess unlabeled probe and by super-shifting with specific antibody for CREB. Loading controls of nuclear proteins were verified by immunoblot of total CREB. C, cold probe control; S, supershift.

From ODE to influence graph with Petri nets theory

Numerical simulation and mapping of results onto graph

Petri net model

Interaction graph

In�uence graph

Dynamic graphs

Implementation of model in Virtual Cell Numerical data

Mathematical model

Supplementary Figure S6Figure S6. Process for building dynamic graphs and visual summary of the associated computa-tional methods. Schema of the different steps to build a dynamic graph from a mathematical model using Petri net theory. There are two parallel series of steps. In the first series, the mathematical model is converted into a Petri net model. An undirected interaction graph and then an influence graph are built using p- and t-invariant analysis. In the second series, the mathematical model is simulated using Virtual Cell. Shading (coloration) for the nodes and edges of the influence graph are computed from the numeri-cal simulation data as explained in Supplementary methods: Dynamics Graphs. The result is a set of graphs with nodes and edges of varying shades that are assembled together to form a dynamic graph.

Figure S7: Dynamic graphs of individual component and motif activities. (A) Dynamic graphs that highlight the activity and flux levels of the three feedforward motifs (FFMs) upon -adrenergic receptor stimulation under baseline conditions (top), PKA inhibition (middle), and MEK inhibition (bottom). Fig. S7A is the interactive duplicate of Fig. 4. The FFMs are shown as diamonds and the components in the pathway are shown as ovals. The activities of the simulated feedforward motifs (diamonds) are depicted with color-coded scales; cAMP and CREB activities are depicted in grayscale. The intensity of the relationship lines represents the percent of the activity through that reaction with dashed lines representing indirect and solid lines representing direct interactions. (B) Dynamic graph of the complete model showing isoproterenol (ISO)-stimulated activity and flux levels for individual components and reactions, respectively. Graph was built from simulation data of the computational model at baseline conditions with ISO stimulation. The dashed arc represents an interaction by an unknown direct or indirect mechanism. Dashed borders represent boundaries between membrane, cytoplasmic, and nuclear compartments. The time shown is the simulation time. (C) Dynamic graph of FFM1 between cAMP and MEK after isoproterenol stimulation. (D) Dynamic graph of FFM1 between cAMP and MEK after isoproterenol stimulation with inhibition of PKA. (E) Dynamic graph of FFM2 between cAMP and MAPK after isoproterenol stimulation. (F) Dynamic graph of FFM2 between cAMP and MAPK after isoproterenol stimulation with inhibition of PKA. (G) Dynamic graph of FFM3 between cAMP and PKA after isoproterenol stimulation. (H) Dynamic graph of nested FFMs between cAMP and CREB after isoproterenol stimulation. (I) Dynamic graph of nested FFMs between cAMP and CREB after isoproterenol stimulation with inhibition of PKA. (J) Dynamic graph of nested FFMs between cAMP and CREB after isoproterenol stimulation with inhibition of MEK. Note: In the electronic version, all the dynamic graphs in this figure are interactive, and they can be animated by the control panels at the bottom. This function is available only in Adobe Acrobat Reader 6 or higher.



A) Note: Click on the network diagrams on the left to animate (available only in Adobe Acrobat 6 or higher)

CREB

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Activation of bRaf by PKA and Activation of bRaf by cAMP-GEF onlycAMP-GEF

E) Feedforward motif 2, with Iso F) Feedforward motif 2, with Iso + Rp-cAMP

cAMP regulation of activator and cAMP regulation of activator anddeactivator of MAPK deactivator of MAPK

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Figure S8. Relative contribution of FFM paths and their lifetimes. (A) Lifetime of the feedforward motifs for the MAPK path to CREB when PKA is not oparative (top panel), for the PKA direct path to CREB (middle panel) and for the both paths to CREB (bottom panel). Start and end points of lifetime bars are determined with the amplification values computed as described in Supplemental Methods: Compu-tational Assessment of Motif Lifetime. The color of the lifetime bars refers to the color of the motifs as shown in Fig. 3 and 4. (B) The larger feedforward motif formed by nesting of the three smaller motifs, and the signal propagation paths for each arm. Grayed nodes and paths are inoperative. The widths of the interaction arrows in the bottom network represent the relative contribution of each path to the activation of effectors; the contribution of each path is quantified by the integrals of motif lifetimes represented in the bar graph in panel A. (C) Relative contribution of the two phosphorylation paths of MEK (left) and CREB (right). The values were computed by integration over time of the phosphorylation rates of the corre-sponding reactions.

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Figure S9. Spread of RT-PCR and morphometric data for animal studies. (A) Spread of raw cycle numbers (GAPDH subtracted) for podocyte differentiation markers synaptopodin (SYNPO), nephrin (NPHS1), and WT-1 (WT1). (B) Spread of foot process density (distance normalized number of foot processes around a glomerular capillary per unit length) as quantified by a blinded observer from 5,000X transmission electron microscope images for the four different treatment groups.

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Figure S10. High magnification transmission electron microscope (TEM) images showing in vivo actin bundles. Super high resolution (50,000X) TEM images showing foot process cytoskeletal integrity in (A) control, (B) puromycin, (C) rolipram treatment after puromycin, and (D) rolipram plus AZD6244 co-treatment after puromycin. Green arrows point to actin bundles that are critical in maintenance of specialized foot process morphology (scale bar = 200 nm).

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Table S1. Proteins that were significantly up- or down-regulated according to differential proteomics of glomeruli from control (saline-injected) and puromycin-injected rats. The raw proteomics data from two separate experiments are available at the Systems Biology Center New York (SBCNY) website (http://sbcny.org/supplementary_materials.htm).

Identified Protein Name

Uniprot Accession

Number

MW Percent Coverage

Number of

Unique Peptides

Protein ID

Probability

No of Spectra

Gene ID Control Puromycin ΔLog2

Protein Nebl (Fragment)

F1LVX3_RAT 19 kDa 56% 5 100% 28 Nebl 1 0.4 -1.3

Protein Gm2a D3ZR01_RAT 21 kDa 35% 5 100% 14 Gm2a 1 0.5 -1.0

Glycine amidinotransferase, mitochondrial

GATM_RAT 48 kDa 54% 20 100% 254 Gatm 1 0.5 -1.0

Ficolin-1 FCN1_RAT 37 kDa 17% 4 100% 24 Fcn1 1 0.5 -1.0

Aminoacylase-1A ACY1A_RAT 46 kDa 13% 3 100% 4 Acy1a 1 0.5 -1.0

RCG20695, isoform CRA_b

D4A4W6_RAT 13 kDa 22% 2 100% 4 Slirp 1 0.6 -0.7

Protein Slc25a13 (Fragment)

F1LZW6_RAT 74 kDa 23% 9 100% 18 Slc25a13 1 0.6 -0.7

Solute carrier family 23 member 1 S23A1_RAT 65 kDa 2% 2 100% 4 Slc23a1 1 0.6 -0.7

40S ribosomal protein S13 RS13_RAT 17 kDa 19% 2 100% 6 Rps13 1 0.6 -0.7

Rho-associated protein kinase 2

D3ZZU3_RAT 167 kDa 2% 2 100% 5 Rock2 1 0.6 -0.7

LRRGT00043 Q6TXF6_RAT 95 kDa 6% 4 100% 6 Rab11fip3 1 0.6 -0.7

Atrial natriuretic peptide receptor 3

ANPRC_RAT 60 kDa 16% 6 100% 19 Npr3 1 0.6 -0.7

Cytochrome c oxidase subunit 2

Q8SEZ5_RAT 26 kDa 16% 4 100% 27 Mt-co2 1 0.6 -0.7

3-mercaptopyruvate sulfurtransferase THTM_RAT 33 kDa 25% 5 100% 26 Mpst 1 0.6 -0.7

Membrane-associated guanylate kinase, WW and PDZ domain-containing protein 2

F1LN71_RAT 139 kDa 22% 17 100% 52 Magi2 1 0.6 -0.7

Isoamyl acetate-hydrolyzing esterase 1 homolog

IAH1_RAT 28 kDa 14% 3 100% 5 Iah1 1 0.6 -0.7

Histone H1.2 H12_RAT 22 kDa 13% 3 100% 19 Hist1h1c 1 0.6 -0.7

Histone H1.0 H10_RAT 21 kDa 19% 3 100% 6 H1f0 1 0.6 -0.7

Protein Gldc D3ZJJ9_RAT 114 kDa 16% 10 100% 22 Gldc 1 0.6 -0.7

Disabled homolog 2 DAB2_RAT 82 kDa 16% 7 100% 16 Dab2 1 0.6 -0.7

Decay accelarating factor 1, isoform CRA_b

G3V6H8_RAT 47 kDa 7% 2 100% 5 Cd55 1 0.6 -0.7

Fructose-bisphosphate aldolase

Q66HT1_RAT 40 kDa 32% 10 100% 31 Aldob 1 0.6 -0.7

Disintegrin and metalloproteinase domain-containing protein 17

ADA17_RAT 93 kDa 6% 2 100% 3 Adam17 1 0.6 -0.7

Acyl-CoA synthetase family member 2, mitochondrial

ACSF2_RAT 68 kDa 14% 5 100% 12 Acsf2 1 0.6 -0.7

Protein Vill D3Z8F1_RAT 97 kDa 17% 8 100% 13 Vill 1 0.7 -0.5

Protein Vil1 B5DFA0_RAT 93 kDa 17% 8 100% 16 Vil1 1 0.7 -0.5

Trimethyllysine dioxygenase, mitochondrial

TMLH_RAT 50 kDa 14% 3 100% 9 Tmlhe 1 0.7 -0.5

Sulfite oxidase G3V6R5_RAT 61 kDa 32% 8 100% 18 Suox 1 0.7 -0.5

Protein Sptbn1 (Fragment)

F1LRX5_RAT 268 kDa 56% 2 100% 9 Sptbn1 1 0.7 -0.5

Serine hydroxymethyltrans

Q5U3Z7_RAT 56 kDa 36% 10 100% 24 Shmt2 1 0.7 -0.5

Protein Vil1 B5DFA0_RAT 93 kDa 17% 8 100% 16 Vil1 1 0.7 -0.5

Trimethyllysine dioxygenase, mitochondrial

TMLH_RAT 50 kDa 14% 3 100% 9 Tmlh

e 1 0.7 -0.5

Sulfite oxidase G3V6R5_RAT 61 kDa 32% 8 100% 18 Suox 1 0.7 -0.5

Protein Sptbn1 (Fragment)

F1LRX5_RAT

268 kDa 56% 2 100% 9 Sptbn

1 1 0.7 -0.5

Serine hydroxymethyltransferase

Q5U3Z7_RAT 56 kDa 36% 10 100% 24 Shmt

2 1 0.7 -0.5

Protein Serpinf1 (Fragment)

F1LSW0_RAT 44 kDa 8% 2 100% 3 Serpi

nf1 1 0.7 -0.5

Protein Rpl10l D4A1P2_RAT 25 kDa 36% 7 100% 30 Rpl10

l 1 0.7 -0.5

Protein Robo2 (Fragment)

F1LN24_RAT

151 kDa 12% 11 100% 23 Robo

2 1 0.7 -0.5

Ribonuclease 4 RNAS4_RAT 17 kDa 22% 3 100% 9 Rnas

e4 1 0.7 -0.5

Protein RGD1312026

D4A563_RAT

191 kDa 2% 2 100% 2

RGD1312026

1 0.7 -0.5

Protein Ptpro Q62797_RAT

138 kDa 10% 8 100% 33 Ptpro 1 0.7 -0.5

Probable proline dehydrogenase 2

B0BNG1_RAT 51 kDa 9% 3 100% 6 Prodh

2 1 0.7 -0.5

Protein Ppa2 D4A830_RAT 38 kDa 42% 10 100% 29 Ppa2 1 0.7 -0.5

Protein Plekhg1 D4AE81_RAT

155 kDa 4% 3 100% 4 Plekh

g1 1 0.7 -0.5

Na(+)/H(+) exchange regulatory cofactor NHE-RF3

NHRF3_RAT 57 kDa 52% 18 100% 70 Pdzk

1 1 0.7 -0.5

Protein Pard3b (Fragment)

F1LW22_RAT

115 kDa 27% 19 100% 55 Pard3

b 1 0.7 -0.5

Phenylalanine-4-hydroxylase

PH4H_RAT 52 kDa 11% 3 100% 4 Pah 1 0.7 -0.5

Platelet-activating factor acetylhydrolase IB subunit alpha (Fragment)

F1LPG0_RAT 32 kDa 13% 2 100% 4 Pafah

1b1 1 0.7 -0.5

Succinyl-CoA:3-ketoacid-coenzyme A transferase 1, mitochondrial

SCOT1_RAT 56 kDa 46% 14 100% 104 Oxct1 1 0.7 -0.5

Protein Nipsnap1

D4A867_RAT 37 kDa 25% 5 100% 12 Nipsn

ap1 1 0.7 -0.5

NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 11

NDUAB_RAT 15 kDa 28% 2 100% 4 Ndufa

11 1 0.7 -0.5

Sodium-dependent glucose transporter 1

NAGT1_RAT 52 kDa 7% 2 100% 7 Naglt

1 1 0.7 -0.5

Uncharacterized protein (Fragment)

F1M111_RAT

202 kDa 3% 3 100% 4 Myo5

c 1 0.7 -0.5

Mitochondrial peptide methionine sulfoxide reductase

MSRA_RAT 26 kDa 11% 2 100% 2 Msra 1 0.7 -0.5

Uncharacterized protein

F1LPX0_RAT 81 kDa 4% 2 100% 8 Mipe

p 1 0.7 -0.5

Malate dehydrogenase, cytoplasmic

MDHC_RAT 36 kDa 15% 4 100% 6 Mdh1 1 0.7 -0.5

Putative lysozyme C-2

F1M8E9_RAT 17 kDa 38% 4 100% 23 Lyz2 1 0.7 -0.5

Protein Lrp1 G3V928_RAT

505 kDa 2% 4 100% 6 Lrp1 1 0.7 -0.5

Protein LOC100363713

D4A412_RAT 15 kDa 17% 2 100% 2

LOC100363713

1 0.7 -0.5


D3ZKG1_RAT 83 kDa 8% 3 100% 11

LOC100361295

1 0.7 -0.5


D3ZHD8_RAT 24 kDa 16% 2 100% 5

LOC100359960

1 0.7 -0.5

Legumain LGMN_RAT 49 kDa 20% 5 100% 36 Lgmn 1 0.7 -0.5

L-lactate dehydrogenase B chain

LDHB_RAT 37 kDa 17% 3 100% 5 Ldhb 1 0.7 -0.5

Integral membrane protein 2B

ITM2B_RAT 30 kDa 20% 3 100% 8 Itm2b 1 0.7 -0.5

IQ motif containing GTPase activating protein 1 (Predicted), isoform CRA_b

G3V7Q7_RAT

189 kDa 28% 29 100% 124 Iqgap

1 1 0.7 -0.5

10 kDa heat shock protein, mitochondrial

CH10_RAT 11 kDa 45% 5 100% 18 Hspe

1 1 0.7 -0.5

Maleylacetoacetate isomerase

MAAI_RAT 24 kDa 14% 3 100% 5 Gstz1 1 0.7 -0.5

Uncharacterized protein (Fragment)

F1LQY0_RAT 46 kDa 37% 9 100% 27 Gsr 1 0.7 -0.5

Beta-galactosidase

D3ZUM4_RAT 73 kDa 8% 3 100% 5 Glb1 1 0.7 -0.5

Fructose-1,6-bisphosphatase 1

F16P1_RAT 40 kDa 35% 9 100% 33 Fbp1 1 0.7 -0.5

Erythrocyte protein band 4.1-like 3

A3E0T0_RAT 97 kDa 26% 17 100% 55 Epb4.

1l3 1 0.7 -0.5

Ectonucleotide pyrophosphatase/phosphodiesterase family member 1

ENPP1_RAT

103 kDa 3% 2 100% 3 Enpp

1 1 0.7 -0.5

EH domain-containing protein 1

EHD1_RAT 61 kDa 47% 7 100% 12 Ehd1 1 0.7 -0.5

Aspartyl aminopeptidase

Q4V8H5_RAT 53 kDa 10% 3 100% 8 Dnpe

p 1 0.7 -0.5

2,4-dienoyl-CoA reductase, mitochondrial

DECR_RAT 36 kDa 14% 4 100% 6 Decr1 1 0.7 -0.5

D-dopachrome decarboxylase

DOPD_RAT 13 kDa 32% 2 100% 3 Ddt 1 0.7 -0.5

Dendrin DEND_RAT 76 kDa 16% 8 100% 28 Ddn 1 0.7 -0.5

N(G),N(G)-dimethylarginine dimethylaminohydrolase 1

DDAH1_RAT 31 kDa 11% 2 100% 3 Ddah

1 1 0.7 -0.5

Bifunctional ATP-dependent dihydroxyacetone kinase/FAD-AMP lyase (cyclizing)

DHAK_RAT 59 kDa 6% 2 100% 5 Dak 1 0.7 -0.5

Cytochrome P450 4A2

CP4A2_RAT 58 kDa 36% 12 100% 67 Cyp4

a2 1 0.7 -0.5

Cytochrome c, somatic

CYC_RAT 12 kDa 49% 5 100% 88 Cycs 1 0.7 -0.5

Cubilin CUBN_RAT

399 kDa 2% 4 100% 7 Cubn 1 0.7 -0.5

Cathepsin B CATB_RAT 37 kDa 29% 8 100% 18 Ctsb 1 0.7 -0.5

Protein Cpsf6 D3ZPL1_RAT 59 kDa 7% 2 100% 6 Cpsf6 1 0.7 -0.5

Coatomer subunit beta'

COPB2_RAT

103 kDa 4% 2 100% 3 Copb

2 1 0.7 -0.5

Catechol O-methyltransferase

COMT_RAT 30 kDa 16% 3 100% 4 Comt 1 0.7 -0.5

Argininosuccinate synthase

ASSY_RAT 46 kDa 25% 6 100% 25 Ass1 1 0.7 -0.5

Argininosuccinate lyase

ARLY_RAT 52 kDa 6% 2 100% 8 Asl 1 0.7 -0.5

Protein Ank3 (Fragment)

F1LM13_RAT

195 kDa 8% 8 100% 14 Ank3 1 0.7 -0.5

Protein AMBP AMBP_RAT 39 kDa 10% 2 100% 3 Ambp 1 0.7 -0.5

Alpha-aminoadipic semialdehyde dehydrogenase

AL7A1_RAT 59 kDa 41% 16 100% 55 Aldh7

a1 1 0.7 -0.5

Aflatoxin B1 aldehyde reductase member 2

ARK72_RAT 41 kDa 17% 5 100% 16 Akr7a

2 1 0.7 -0.5

Adenylate kinase isoenzyme 4, mitochondrial

KAD4_RAT 25 kDa 30% 6 100% 19 Ak4 1 0.7 -0.5

Protein Agphd1 D3ZUX1_RAT 42 kDa 15% 3 100% 7 Agph

d1 1 0.7 -0.5

Protein Acss1 D3ZZN3_RAT 75 kDa 19% 7 100% 23 Acss

1 1 0.7 -0.5

Protein Acsf3 D3ZUX7_RAT 65 kDa 5% 2 98% 4 Acsf3 1 0.7 -0.5

von Willebrand factor A domain-containing protein 1

VWA1_RAT 45 kDa 6% 3 100% 6 Vwa1 1 1.4 0.5

Transthyretin TTHY_RAT 16 kDa 52% 5 100% 5 Ttr 1 1.4 0.5

Two pore calcium channel protein 1 (Fragment)

F1LNS4_RAT 59 kDa 9% 3 100% 8 Tpcn

1 1 1.4 0.5

Protein Sqrdl (Fragment)

F1LLX4_RAT 36 kDa 8% 2 100% 3 Sqrdl 1 1.4 0.5

Sorbitol dehydrogenase

DHSO_RAT 38 kDa 8% 2 100% 6 Sord 1 1.4 0.5

Protein Slc43a2 D3ZDC2_RAT 63 kDa 6% 3 100% 3 Slc43

a2 1 1.4 0.5

Protein Slc25a24 B1WC67_RAT 53 kDa 13% 4 100% 13 Slc25

a24 1 1.4 0.5

U4/U6.U5 tri-snRNP-associated protein 1

SNUT1_RAT 91 kDa 6% 3 100% 16 Sart1 1 1.4 0.5

Reticulon-4 D3ZT22_RAT 41 kDa 20% 5 100% 64 Rtn4 1 1.4 0.5

Protein kinase C delta-binding protein

PRDBP_RAT 28 kDa 10% 2 100% 2 Prkcd

bp 1 1.4 0.5


F1LPS3_RAT 74 kDa 4% 2 100% 4 Nolc1 1 1.4 0.5

Myl9 protein B0BMS8_RAT 20 kDa 54% 4 100% 25 Myl9 1 1.4 0.5

Myosin-11 E9PTI3_RAT

228 kDa 13% 5 100% 8 Myh1

1 1 1.4 0.5

Protein Luc7l (Fragment)

F1LNK3_RAT 42 kDa 9% 2 100% 3 Luc7l 1 1.4 0.5

Heterochromatin protein 1-binding protein 3

F1M6V1_RAT 61 kDa 10% 4 100% 7 Hp1b

p3 1 1.4 0.5

Golgin subfamily A member 4

F1LPQ7_RAT

257 kDa 2% 2 100% 2 Golga

4 1 1.4 0.5

Guanine nucleotide-binding protein subunit gamma

Q3KRE3_RAT 7 kDa 53% 2 100% 4 Gng1

0 1 1.4 0.5

Guanine nucleotide-binding protein G(q) subunit alpha

D4AE68_RAT 31 kDa 26% 4 100% 9 Gnaq 1 1.4 0.5

Gamma-glutamyltransferase 5

GGT5_RAT 62 kDa 17% 4 100% 29 Ggt5 1 1.4 0.5

Band 4.1-like protein 1

D3ZL93_RAT

171 kDa 2% 2 100% 2 Epb4

1l1 1 1.4 0.5

ELAV (Embryonic lethal, abnormal vision, Drosophila)-like 1 (Hu antigen R)

B5DF91_RAT 36 kDa 10% 2 100% 4 Elavl

1 1 1.4 0.5

Cytochrome b5 reductase 1

G3V9S0_RAT 34 kDa 17% 3 100% 5 Cyb5r

1 1 1.4 0.5

Protein Ckap4 D3ZH41_RAT 64 kDa 15% 5 100% 16 Ckap

4 1 1.4 0.5

CUGBP Elav-like family member 1

CELF1_RAT 52 kDa 6% 2 100% 3 Celf1 1 1.4 0.5

Protein Bag2 (Fragment)

F1LQH9_RAT 19 kDa 19% 2 100% 3 Bag2 1 1.4 0.5

Acid ceramidase ASAH1_RAT 44 kDa 19% 5 100% 6 Asah

1 1 1.4 0.5

Apolipoprotein H

Q5I0M1_RAT 38 kDa 22% 5 100% 12 Apoh 1 1.4 0.5

Protein Ahnak D3ZN29_RAT 53 kDa 34% 11 100% 19 Ahna

k 1 1.4 0.5

Acid phosphatase-like protein 2

ACPL2_RAT 55 kDa 5% 2 100% 3 Acpl2 1 1.4 0.5

Protein S100-A11

S10AB_RAT 11 kDa 28% 2 100% 22 S100

a11 1 1.5 0.6

Nestin, isoform CRA_b

G3V8F8_RAT

209 kDa 50% 69 100% 402 Nes 1 1.5 0.6

MOSC domain-containing protein 2, mitochondrial

MOSC2_RAT 38 kDa 15% 2 100% 3 Marc

2 1 1.5 0.6

Keratin complex 2, basic, gene 7, isoform CRA_a

G3V712_RAT 51 kDa 11% 3 100% 6 Krt7 1 1.5 0.6

Heat shock 70 kDa protein 1A/1B (Fragment)

F1LPF5_RAT 70 kDa 18% 4 100% 7 Hspa

1a 1 1.5 0.6

High mobility group nucleosome-binding domain-containing protein 5

HMGN5_RAT 49 kDa 20% 4 100% 6 Hmgn

5 1 1.5 0.6

Four and a half LIM domains protein 2

FHL2_RAT 32 kDa 36% 9 100% 18 Fhl2 1 1.5 0.6

Endoplasmic reticulum aminopeptidase 1

ERAP1_RAT

106 kDa 4% 2 100% 3 Erap1 1 1.5 0.6

NADH-cytochrome b5 reductase 3

NB5R3_RAT 34 kDa 54% 12 100% 56 Cyb5r

3 1 1.5 0.6

Ceruloplasmin D3ZZX3_RAT

124 kDa 12% 9 100% 31 Cp 1 1.5 0.6

Phosphatidate cytidylyltransferase 2

CDS2_RAT 51 kDa 16% 5 100% 10 Cds2 1 1.5 0.6

C4b-binding protein alpha chain

C4BPA_RAT 62 kDa 20% 10 100% 34 C4bp

a 1 1.5 0.6

Annexin A3 ANXA3_RAT 36 kDa 44% 11 100% 35 Anxa

3 1 1.5 0.6

Disintegrin and metalloproteinase domain-containing protein 15

ADA15_RAT 93 kDa 3% 2 100% 4 Adam

15 1 1.5 0.6

Actin, alpha cardiac muscle 1

ACTC_RAT 42 kDa 63% 7 100% 38 Actc1 0.9 1.5 0.6

Tropomyosin beta chain (Fragment)

F1LRB1_RAT 29 kDa 38% 2 98% 3 Tpm2 1 1.6 0.7

Lamina-associated polypeptide 2, isoform beta

D3ZNL2_RAT 75 kDa 19% 2 100% 3 Tmpo 1 1.6 0.7

Spectrin alpha chain, brain

SPTA2_RAT

285 kDa 63% 127 100% 924 Sptan

1 1 1.6 0.7

Protein Pnn D3ZAY8_RAT 83 kDa 9% 4 100% 4 Pnn 1 1.6 0.7

Galectin-1 LEG1_RAT 15 kDa 45% 5 100% 20 Lgals

1 1 1.6 0.7

Eukaryotic translation initiation factor 2, subunit 2 (Beta)

Q6P685_RAT 38 kDa 14% 3 100% 5 Eif2s

2 1 1.6 0.7

CD34 antigen (Predicted)

B1PLB1_RAT 41 kDa 17% 3 100% 17 Cd34 1 1.6 0.7

ATP synthase subunit d, mitochondrial

ATP5H_RAT 19 kDa 43% 6 100% 29 Atp5h 1 1.6 0.7

Aquaporin-1 AQP1_RAT 29 kDa 20% 2 100% 7 Aqp1 1 1.6 0.7

Plasminogen PLMN_RAT 91 kDa 3% 2 100% 4 Plg 1 1.7 0.8

Peroxisomal membrane protein PEX14

PEX14_RAT 41 kDa 13% 2 100% 4 Pex1

4 1 1.7 0.8

Myeloid-associated differentiation marker

MYADM_RAT 35 kDa 9% 2 100% 21 Myad

m 1 1.7 0.8

Granulin, isoform CRA_c

G3V8V1_RAT 65 kDa 6% 2 100% 8 Grn 1 1.7 0.8

Cathepsin D 34 kDa heavy chain

D3ZGP8_RAT 48 kDa 17% 5 100% 16 Ctsd 1 1.7 0.8

Vitamin K-dependent protein S

PROS_RAT 75 kDa 9% 5 100% 9 Pros1 1 1.8 0.8

Gamma-synuclein

D4ACB0_RAT 13 kDa 26% 2 100% 4 Sncg 1 2 1.0

Protein FAM151A

F151A_RAT 67 kDa 5% 2 100% 2 Fam1

51a 1 2 1.0

Hemopexin HEMO_RAT 51 kDa 10% 3 100% 4 Hpx 1 2.2 1.1

Protein Cfh F1M983_RAT

140 kDa 3% 2 100% 3 Cfh 1 2.4 1.3

Alpha-1-macroglobulin

A1M_RAT

167 kDa 7% 5 100% 19 A1m 1 2.4 1.3

Desmin DESM_RAT 53 kDa 61% 19 100% 111 Des 1 2.7 1.4

Apolipoprotein A-I

APOA1_RAT 30 kDa 16% 3 100% 8 Apoa

1 1 2.8 1.5

Serine protease inhibitor A3N

SPA3N_RAT 47 kDa 9% 3 100% 8 Serpi

na3n 1 2.9 1.5

Complement C3 CO3_RAT

186 kDa 16% 16 100% 34 C3 1 3 1.6

Alpha-2-HS-glycoprotein

FETUA_RAT 38 kDa 28% 5 100% 50 Ahsg 1 3 1.6

Fibrinopeptide A D3ZJ95_RAT 87 kDa 15% 8 100% 22 Fga 1 3.6 1.8

Inter alpha-trypsin inhibitor, heavy chain 4

Q5EBC0_RAT

104 kDa 5% 3 100% 5 Itih4 1 3.7 1.9

Serine protease inhibitor A3L

SPA3L_RAT 46 kDa 13% 2 100% 4 Serpi

na3l 1 4.1 2.0

Fibrinogen gamma chain

FIBG_RAT 51 kDa 31% 10 100% 29 Fgg 1 4.1 2.0

Serine protease inhibitor A3K

SPA3K_RAT 47 kDa 25% 5 100% 6 Serpi

na3k 1 4.2 2.1

Protein Synpo2l D3ZZ68_RAT

103 kDa 5% 3 100% 7 Synp

o2l 1 4.5 2.2


D3Z8Y5_RAT 54 kDa 40% 13 100% 40 Fgb 1 4.5 2.2

Serum albumin ALBU_RAT 69 kDa 52% 27 100% 259 Alb 1.1 4.5 2.2

Alpha-1-antiproteinase

A1AT_RAT 46 kDa 21% 5 100% 29 Serpi

na1 1 4.7 2.2

Alpha-1-inhibitor 3

A1I3_RAT

164 kDa 8% 8 100% 39 A1i3 1 5.8 2.5

Table S2. Abundance of different PKA subunits as measured by the two independent proteomic experiments. Note that one-peptide hits below were not included in the general proteomic analysis.

Name Uniprot ID Size # Pep. ID Pr. Gene ID Level

First Experiment

cAMP-dependent protein kinase type I-alpha regulatory subunit KAP0_RAT 43 kDa 4 98% Prkar1a 1.2

cAMP-dependent protein kinase type II-alpha regulatory subunit KAP2_RAT 46 kDa 4 100% Prkar2a 1.2

cAMP-dependent protein kinase type II-beta regulatory subunit KAP3_RAT 46 kDa 1 86% Prkar2b 0.8

5'-AMP-activated protein kinase subunit beta-1 AAKB1_RAT 30 kDa 1 78% Prkab1 0.8

5'-AMP-activated protein kinase subunit gamma-1 AAKG1_RAT 37 kDa 1 88% Prkag1 0.9

Second Experiment

cAMP-dependent protein kinase type I-alpha regulatory subunit KAP0_RAT 43 kDa 5 100% Prkar1a 1.1

cAMP-dependent protein kinase type II-beta regulatory subunit KAP3_RAT 46 kDa 1 50% Prkar2b 1.1

Protein kinase, cAMP-dependent, regulatory, type 2, alpha, isoform CRA_a G3V8Q6_RAT 45 kDa 3 100% Prkar2a 1.2

5'-AMP-activated protein kinase subunit gamma-1 AAKG1_RAT 37 kDa 1 50% Prkag1 0.8

5'-AMP-activated protein kinase catalytic subunit alpha-1 AAPK1_RAT 64 kDa 2 100% Prkaa1 1

Protein kinase, cAMP-dependent, catalytic, alpha A1L1M0_RAT 41 kDa 1 50% Prkaca 1

Table S3. Simulation parameters for the computational model. This model is accessible in the Virtual Cell database under the username sihar and the name Podocyte Nested FFM Model. Reac. No.

Reaction Name (enzyme)

Reaction Type

kf (µM-s)

-1 kb (s-1)

KD or KM (µM)

kcat (s-1)

References Comments

Nucleus 1 MSK → MSK*

(MAPK*nuc) catalysis NA NA 25 10 (53, 54)

2 MSK* → MSK mass action 0.04 s-1 0 NA NA Constrained from the time course of CREB activation.

3 CREB → CREB* (PKAnuc)

catalysis NA NA 17 6 (21) Reference found Km ~ 17 µM. kcat was constrained by experimental PKA, MAPK and CREB data.

4 CREB → CREB* (MSK*) catalysis NA NA 2 1.5 (21) Reference found Km ~ 2 µM. kcat was constrained by experimental PKA, MAPK and CREB data.

5 CREB* → CREB (PP2Anuc)

catalysis NA NA 15.66 6 (55, 56)

6 CREB* → CREB (PP1Anuc)

catalysis NA NA 3 0.4 (57)

7 MKP1 gene → MKP1 RNA (MAPK*nuc)

catalysis NA NA 4 0.0003

(4) This step is a “black box” that accounts for the negative feedback loop involved in shutting down MAPK activity. Reference modeled this process with Km ~ 4 µM and kcat ~ 0.0008 s-1. The number used was partly constrained by the observed duration of MAPK activity in podocytes.

8 MKP1 gene → MKP1 RNA (basal transcription)

mass action 2 x 10-6 s-1

0 NA NA (4) See note for reaction 7

9 MAPK* → MAPKthr (MKP2)

catalysis NA NA 0.0667 1 (58)

10 MAPK* → MAPKthr (MKP1)


11 MAPK* → MAPKthr (MKP1*)


12 MAPKthr → MAPK (MKP2)


13 MAPKthr → MAPK (MKP1)


14 MAPKthr → MAPK (MKP1*)


15 MKP1→ MKP1* (MAPK*)


16 MKP1* → MKP1 mass action 0.0001s-

1 0 NA NA (4) Constrained by timecourse from

literature 17 MKP1 degradation mass action 0.00037

s-1 0 NA NA (59)

18 MKP1* degradation mass action 0.0001s-

1 0 NA NA (59)

19 PKA + PKI ↔ PKI.PKA mass action 1 0.0001 NA NA (60) Reference found Ki ~ 0.1nM

Cytoplasm 20 MKP1 RNA → MKP1 mass action 0.004 0 NA NA Constrained by experimental MAPK

data 21 MAPKK → MAPKK ser

(B-Raf*) catalysis NA NA 0.159 0.105 (61) Kinetics from c-Raf

22 MAPKK ser → MAPKK* (B-Raf*)

catalysis NA NA 0.159 0.105 (61) Kinetics from c-Raf

23 MAPK → MAPK tyr (MAPKK *)

catalysis NA NA 0.046296

0.15 (62, 63)

24 MAPK tyr → MAPK* (MAPKK *)

catalysis NA NA 0.046296

0.15 (62, 63)

25 cAMP → AMP (PDE) catalysis NA NA 1.3 8 (64) 26 cAMP → AMP (PDE*) catalysis NA NA 1.3 20 (65) 27 cAMP → AMP

(PDEhighKM) catalysis NA NA 15 8 (26) Constrained by timecourse from

literature 28 B-Raf → B-Raf* (PKAcyt) catalysis NA NA 1 0.1 Constrained by experimental MAPK

data 29 B-Raf* → B-Raf (PP2A) catalysis NA NA 15.66 6 (55, 56) 30 PTP-SL → PTP-SL*

(PKAcyt) catalysis NA NA 0.1 0.2 (66)

31 PTP-SL* → PTP-SL (PP1)

catalysis NA NA 6 5 (67)

32 MAPKK* → MAPKK ser (PP2Acyt)


33 MAPKK ser → MAPKK (PP2Acyt)


34 MAPK* → MAPK tyr (MKP1)


35 MAPK tyr → MAPK (MKP1)


36 MAPK* → MAPK tyr (MKP1*)


37 MAPK tyr → MAPK (MKP1*)


38 MAPK* → MAPK tyr (MKP2)


39 MAPK tyr → MAPK (MKP2)


40 MAPK* → MAPK tyr (PTP-SL)


41 MKP1→ MKP1* (MAPK*)


42 MKP1* → MKP1 mass action 0.0001s-

1 0 NA NA (4) Constrained by timecourse from

literature 43 MKP1 degradation mass action 0.00037

s-1 0 NA NA (59)

44 MKP1* degradation mass action 0.0001s-

1 0 NA NA (59)

45 PDE → PDE* (PKAcyt) catalysis NA NA 0.5 9 (69) 46 PDE* → PDE (PDEPP) catalysis NA NA 0.96 0.77 (37) Constrained by timecourse from

literature 47 R2C2 + cAMP ↔

cAMP.R2C2 mass action 54 33 NA NA (70, 71)

48 cAMP.R2C2 + cAMP ↔ cAMP2.R2C2

mass action 54 33 NA NA (70, 71)

49 cAMP2.R2C2 + cAMP ↔ cAMP3.R2C2

mass action 75 110 NA NA (72)

50 cAMP3.R2C2 + cAMP ↔ cAMP4.R2C2

mass action 75 32.5 NA NA (72)

51 cAMP4.R2C2 ↔ cAMP4.R2C + PKA

mass action 0.6 s-1 0.18 NA NA (37) Constrained by timecourse from literature

52 cAMP4.R2C ↔ cAMP4.R2 + PKA

mass action 0.6 s-1 0.18 NA NA (37) Constrained by timecourse from literature

53 PKA.PKI ↔ PKA + PKI mass action 0.0001s-

1 0 NA NA (60) Binding of PKA to PKI occurs in

nucleus only. 54 cAMP + EPAC ↔

cAMP.EPAC mass action 32 96 NA NA (73) Reference found Kd ~ 3.3 uM

Golgi Reactions 55 MAPKK → MAPKK ser

(Rap1.Braf) catalysis NA NA 0.4 0.95 Constrained by experimental MAPK

data 56 MAPKK ser → MAPKK*

(Rap1.Braf) catalysis NA NA 0.4 0.95 Constrained by experimental MAPK

data 57 B-Raf + Rap1GTP ↔

Rap1.BRaf mass action 4 10 NA NA Constrained by experimental MAPK

data 58 Rap1GDP ↔ Rap1GTP mass action 3x10-6 8x10-5 NA NA (74, 75) "five orders of magnitude" difference

between GTPase rate ± RapGAP. The rate given here given here were calculated from Kraemer et al (2002) for the above reasons.

59 cAMP.EPAC + Rap1GDP ↔ Rap1.EPAC

mass action 2 0.8 NA NA Constrained by experimental MAPK data

60 Rap1.EPAC → cAMP.EPAC + Rap1GTP

mass action 0.2 0 NA NA Constrained by experimental MAPK data

61 RG1 + Rap1GTP ↔ Rap1.RG1

mass action 0.62 8.7 NA NA (76)

62 Rap1.RG1 → Rap1GDP + RG1

mass action 8 0 NA NA (74, 76)

Plasma Membrane 63 ATP → cAMP (AC.Gsa) catalysis NA NA 3.15 8.5 (77)

64 βAR.iso → βAR.P (GRKPM)

catalysis NA NA 250 0.204 (78) Reference used kcat = 0.2 s-1 and Km = 0.2 µM. Converted the Km to molecule per µm2 as described (see notes).

65 iso + βAR ↔ βAR.iso mass action 0.1 0.1 NA NA (79) Reference estimated the binding affinity to the purified receptor is at about 1 uM, but the conformational change only happens at 30 uM. We will use the former value, since it is already much weaker binding between the receptor and G protein.

66 βAR.iso + Gs trimer ↔ βAR.Gs

mass action 0.01 0.1 NA NA Estimated

67 βAR.Gs → βAR iso + Gsa + Gbg

mass action 0.025 0 NA NA (80, 81) Rate varies, but the first reference suggested a rate ~ 1.5-2.5 per min

68 Gbg + GRKcyt ↔ GRK.Gbg

mass action 1 0.25 NA NA (78) Reaction 68 and 69 describes the recruitment of GRK to the plasma membrane by the beta-gamma subunit. Reference suggested that binding to the beta gamma subunit has affinity ~ 30 nM and is dependent on the presence of phospholipids. We increased the backward rate constant by an order of magnitude to fit experimentally observed data.

69 GRK.Gbg ↔ GRKPM + Gbg

mass action 1 1x10-4 NA NA See reaction 68.

70 GRKPM → GRKcyt mass action 0.01 0 NA NA See reaction 68. 71 Gsa + AC ↔ AC.Gsa mass action 1 3.4 NA NA (82) 72 Gsa → GsaGDP mass action 0.11 0 NA NA (80) Reference reported a rate of 4/min at

30°C (0.11/s at 37°C). 73 GsaGDP + Gbg → Gs

trimer mass action 0.006 0 NA NA Estimated

74 βAR.P → βAR mass action 0.00047 0 NA NA (83) Black box for receptor recycling. Constrained with functional receptor time course from reference.

Note: 1. For reactions on the plasma membrane, we used the conversion factor 1 µM = 1200 molecules per µm2. For reactions on the plasma

membrane, we used the conversion factor 1 µM =600 molecules per µm2. These factors were determined by the geometric parameters of the compartments of the model.

2. Nuclear transport was modeled using the equation [ ] [ ]nucortcytimport xkxkJ ⋅−⋅= exp . The following parameters were used for the simulations: Species kimport kexport Reference Comment MAPK* 0.0175 0.01 (84, 85) Once dually phosphorylated, MAPK is actively imported. First

reference measured a τ of 80 s when MAPK is phosphorylated and a passive import τ of 200 s for inactive MAPK.

MAPK 0.005 0.006 (84, 85) See preceding rate. Export constant takes into account CRM1-mediated export measured in (84).

PKA 0.0075 0.0075 (86, 87) In the first reference, the nuclear PKA level reached the maximum value about 15 minutes post stimulation. In the second experiment, application of forskolin, stimulate CBP-CREB complex formation in < 10 min. after stimulation. Assuming t ½ of about 5 min., the characteristic rate is ~ 0.002 s-1.

PKI.PKA 0.0125 0 (22) Binding of PKA and PKI induces a conformation change exposing and nuclear export sequence. Constrained by experimental PKA and CREB data.

PKI 0.001 0 (22) After stimulation of the cAMP, PKI translocates to the nucleus. Constrained by experimental PKA and CREB data.

MKP1 RNA 1 0 This rate, along with the rate of MKP translation in the cytoplasm is a black box representing the steps involved in MKP-1 negative feedback.

MKP1 0.001 0.001 Constrained by experimental MAPK data MKP1* 0.001 0.001 Constrained by experimental MAPK data

Initial conditions (only species with non-zero initial concentration are shown.) Species compartment Buffered? Concentration unit References comments Iso extracellular

fluid Yes 10 µM Used in the experiment

βAR plasma membrane

No 33 molecules/µm2 A typical number is ~ 10,000-20,000 per cells. Phosphorylated receptor concentrations (Beta-P and beta-IsoP) were set to 1x10-6 µM for computational purposes.

Gs trimer plasma membrane

No 100 molecules/µm2 (88, 89) Quantification in myocytes demonstrated that adenylyl-cyclase is the signaling bottleneck of this pathway, and that Gs is in excess compared to BAR. The value of Gs and the resulting dynamics were adjusted to respect these physiological constraints.

AC plasma membrane

No 100 molecules/µm2 (89)

MAPK cytosol No 0.263 µM (54) R2C2 cytosol No 0.2 µM (90) ATP cytosol Yes 4000 µM (37) Constrained by timecourse from literature MKP1 cytosol No 0.00036 µM Steady state value BRaf cytosol No 0.2 µM (91) Rap1GAP cytosol No 0.15 µM Constrained by experimental MAPK data. MAPKK cytosol No 0.18 µM (62) cAMP cytosol No 1x10-4 µM Basal cAMP concentration, steady state value EPAC cytosol No 0.16 µM Constrained by experimental MAPK activation

time course. [EPAC-cAMP] was set to a very low level (1x10-6 µM) for computational purposes.

PTP-SL cytosol No 0.01 µM Constrained by experimental CREB activation time course.

PP2A cytosol No 0.075 µM Estimated GRK cytosol No 0.045 µM (92) Reference estimated cellular concentration

between 0.01-0.2 µM. PDE cytosol No 0.4 µM (37) Constrained by timecourse from literature MKP2 cytosol No 0.001 µM Estimated

Rap1GDP Golgi membrane

No 100 molecules/µm2 (93) Reference found total cellular Rap1 to be ~ 1 µM. Converting to the number of molecules per area of Golgi membrane gives concentration on the order of ~100 molecules/µm2.The concentrations of Rap1 in complexes (Rap1-RGII, Rap1-EPAC, Rap1-BRaf) were set to 1x10-6 µM

Rap1GTP Golgi membrane

No 0 molecules/µm2 Assumed that all Rap 1 is in the GDP bound state.

MSK Nucleus No 0.1 µM Constrained by experimental CREB output PP1A Nucleus No 0.04 µM Assume the same estimated concentration as

PP2A. MKP1 gene Nucleus Yes 0.2 µM Constrained by experimental MAPK output PP2A Nucleus No 0.05 µM Assume approximately the same concentration

as cytoplasmic. CREB Nucleus No 0.3 µM (86) Note: The following conversion factors were used: 1 µM = 1200 molecules/µm2 (plasma membrane) and 1 µM = 600 molecules/µm2 (Golgi). These factors were determined by the geometric parameters of the compartments of the model.

Table S4. Parameter normalized local sensitivity analysis. Normalized local sensitivity value for a given parameter is defined as “percent change in phospho-CREB concentration for a 1% increase in the listed parameter”. Because these local sensitivity values are of functions of time, maximum absolute value is reported. These values generally represent the local maxima of lower values over time. Sensitivity values of reaction parameters (Reaction number + Parameter name) 1)km -0.455 1)kcat 0.457 2)kf -0.43 3)km -0.085 3)kcat 0.0863 4)km -0.488 4)kcat 0.53 5)km 0.492 5)kcat -0.495 6)km 0.129 6)kcat -0.134 7)km 0.475 7)kcat -0.499 8)kf -0.091 9)km 0.01397 9)kcat -0.0233 10)km 0.0245 10)kcat -0.0287 11)km 0.212 11)kcat -0.256 12)km -0.00376 12)kcat 0.0105 13)km -0.00075 13)kcat 0.00199 14)km -0.022 14)kcat 0.06 15)km 0.00203 15)kcat -0.00203 16)kf 0.0014 17)kf 0.00198 18)kf 0.0233 19)kf -0.368 19)kr 0.00106 20)kf -0.0499 21)km -0.205

21)kcat 0.373 22)km -0.429 22)kcat 0.54 23)km -0.0786 23)kcat 0.3198 24)km -0.223 24)kcat 0.418 25)km 0.185 25)kcat -0.2 26)km 2.779 26)kcat -2.998 27)km 0.166 27)kcat -0.165 28)km -0.699 28)kcat 0.828 29)km 0.838 29)kcat -0.841 30)km -0.044 30)kcat 0.0456 31)km 0.0458 31)kcat -0.0458 32)km 0.7007 32)kcat -0.7013 33)km 0.5012 33)kcat -0.5023 34)km 0.02019 34)kcat -0.02941 35)km 0.0172 35)kcat -0.02671 36)km 0.1279 36)kcat -0.1926 37)km 0.01704 37)kcat -0.1677 38)km 0.01397 38)kcat -0.02334

39)km -0.003756 39)kcat 0.01056 40)km 0.06718 40)kcat -0.06937 41)km 0.003367 41)kcat -0.003367 42)kf 0.003962 43)kf 0.00533 44)kf 0.0069 45)km 0.3449 45)kcat -0.4558 46)km -0.3081 46)kcat 0.3875 47)kf 0.6296 47)kr -0.629 48)kf 0.7388 48)kr -0.758 49)kf 0.758 49)kr -0.7501 50)kr -0.9252 50)kf 0.7561 51)kf 0.7521 51)kr -0.03611 52)kf 0.3565 52)kr -0.3507 53)kr 0.2116 54)kf 0.4026 54)kr -0.4018 55)km -0.1963 55)kcat 0.2734 56)km -0.1985 56)kcat 0.2091 57)kf 0.4688 57)kr -0.4667 58)kf 0.0004555

58)kr -0.0006866 59)kf 0.4258 59)kr -0.3389 60)kf 0.3613 61)kf -0.26 61)kr 0.13 62)kcat -0.1897 63)km -0.0031636 63)kcat 3.367 64)km 1.382 64)kcat -1.391

65)kf 0.288379806 65)kr 0.020341354 66)kf 1.4033564 66)kr -1.1581675 67)kf 2.0 67)kr 0 68)kf -0.2164726 68)kr 0.0534714 69)kf -0.06977 69)kr 0.0161 70)kr 0

71)kf 1.8309 71)kr -1.831 72)kf -1.7926 73)kf 0.024 74)kf 1.1692

Sensitivity values of the parameters of translocation reactions and initial concentration

Translocation Initial Concentrations Initial Concentrations (cont) MAPK* import 0.424 ISO 1.286 PP2A -2.0471 MAPK* export 0.1414 BAR 1.809 GRK -1.389 MAPK import -0.01096 Gs 2.2669 PDE -3.192 MAPK export 0.01622 AC 2.5456 MKP2 -0.1921 PKA import 0.942 MAPK -0.31 RAP1GDP 0.2621 PKA export -0.0855 R2C2 1.40 MSK 0.53 PKI-PKA export 0.01322 ATP 0 PP1A -0.1335 PKI import -1.0236 MKP1 0 MKP1 DNA 0 MKPRNA export -0.00021 Braf 1.084 PP2A nucleus 0.4952 MKP1_import -0.01807 Rap1GAP -0.0364 MKP1_export 0.004312 MEK 0.6764 MKP1*_import -0.1225 EPAC 0.4358 MKP1*_export 0.05891 PTP -0.0703

Table S5. Abundance of glomerular and tubular markers as quantified by proteomic analysis. Spectral counts of podocyte specific proteins were an order of magnitude higher than those of tubular proteins, with a median of 52 unique glomerular spectra vs. 5 tubular spectra (214 ± 136 vs. 23 ± 18; p < 0.001, t-test). Of the 10 tubular proteins, only 5 had 2 or more unique peptides (7 ± 6); whereas all 15 glomerular proteins had 3 or more (17 ± 4), demonstrating high levels of enrichment for glomeruli with only trace amounts of tubular contamination.

TUBULAR MARKERS Gene ID Uniprot ID Size Coverage Peptides ID Prob. Spectra

Megalin* Lrp2 LRP2_RAT 519 kDa 18% 54 100% 165

Aquaporin-1 Aqp1 AQP1_RAT 29 kDa 20% 2 100% 7

Aquaporin-2 Aqp2 AQP2_RAT 29 kDa 0% 0 0% 0

V-ATPase, V1 subunit G1 Atp6v1g1 B2GUV5_RAT 14 kDa 12% 2 100% 6

V-ATPase, V1 subunit D Atp6v1d Q6P503_RAT 28 kDa 16% 3 100% 5

Solute carrier family 12 member 3 Slc12a3 G3V8G0_RAT 111 kDa 1% 1 50% 2

Chloride Channel Voltage-Sensitive 5 Clcn5 CLCN5_RAT 83 kDa 0% 0 0% 0

SGLT-1 Slc5a1 SC5A1_RAT 73 kDa 4% 1 50% 2

SGLT-2 Slc5a2 F1LMI6_RAT 73 kDa 7% 3 100% 23

Mean 9% 7.3 67% 23

SEM 3% 5.8 14% 18

Median 7% 2.0 100% 5

PODOCYTE MARKERS Gene ID Uniprot ID Size Coverage Peptides ID Prob. Spectra

Alpha-actinin-4 Actn4 ACTN4_RAT 105 kDa 80% 72 100% 2086

Protein tryrosine kinase Mer Mertk MERTK_RAT 109 kDa 10% 9 100% 21

Dendrin Ddn DEND_RAT 76 kDa 16% 8 100% 28

IQ motif containing GAP 1 Iqgap1 G3V7Q7_RAT 189 kDa 28% 29 100% 124

Kin of IRRE-like protein 1 Kirrel F1M7V1_RAT 87 kDa 23% 13 100% 38

Magi-2 Magi2 F1LN71_RAT 139 kDa 22% 17 100% 52

Nephrin Nphs1 NPHN_RAT 136 kDa 27% 21 100% 65

Podocalyxin Podxl PODXL_RAT 52 kDa 26% 9 100% 276

Podocin Nphs2 PODO_RAT 42 kDa 47% 14 100% 90

CD2AP Cd2ap F1LRS8_RAT 70 kDa 17% 8 100% 21

Fat1 Fat1 F1LP84_RAT 506 kDa 1% 3 100% 5

Par-3 partitioning defective 3 homolog B Pard3b F1LW22_RAT 115 kDa 27% 19 100% 55

GLEPP1, PTP-RO Ptpro Q62797_RAT 138 kDa 10% 8 100% 33

Semaphorin 3G Sema3g F1LNH0_RAT 87 kDa 12% 5 100% 9

Synaptopodin Synpo SYNPO_RAT 100 kDa 38% 27 100% 307

Mean 26% 17 100% 214

SEM 5% 4 0% 136

Median 23% 13 100% 52

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