Abstract

Purpose: An intricate network of regulatory processes determines the chondrocyte cell fate during development and maintains tissue homeostasis. In the event of a disease such as OA, the regulatory network is critically compromised. To cure the disease, we need to restore the regulatory processes to their original state. However, because of the inherent complexity of regulatory networks, they cannot be efficiently analyzed and understood without computational assistance. To obtain insight into the function of such complex networks we developed a dynamic computational model of chondrocytes, the Executable CHOndrocyte or ECHO. In ECHO cell fates corresponding to osteoarthritis as well as healthy chondrocytes can be investigated. We used ECHO to predict potential targets for switching from an OA-like chondrocyte to a healthy articular chondrocyte.

Methods: We generated a computational model of growth plate chondrocytes (GP model) and a model of articular chondrocytes (AC model) In each model it is possible to set the activity of each of the proteins in the network at a level between 0 and 100 in increments of, for example, 1 or 10. It is also possible to randomly initialize the activities of proteins, or use a combination of random and set initializations. In silico experiments can then be carried out by simulating the evolution of the modelled regulatory network over time. We used ECHO to obtain insight into cross talk of 7 signal transduction pathways important for chondrocyte development and cartilage maintenance: IGF, PTHrP, BMP, FGF, TGFbeta, WNT, IHH. ECHO consists of a network of 123 intracellular signaling molecules (kinases) with 354 interactions. The network faithfully resembles current status of literature. RUNX2+ is the readout for hypertrophy and OA, and SOX9+ the readout of healthy articular chondrocytes. qPCR experiments on human mesenchymal stem cells (hMSCs) and human articular chondrocytes (hACs) were used to validate the model.

Results: Using ECHO we analyzed the most influential pathways, and performed in silico experiments to obtain insight into the molecular mechanisms of cartilage development and disease. For example, we investigated the cell’s response to addition or inhibition of single (Figure 1), or combinations of growth factors or cytokines. Both the GP and AC models showed a dose-dependent response to (combinations of) external stimuli. qPCR validated this dose-dependency in MSC and chondrocytes.We then investigated switching cell state through perturbations of extra-cellular ligands. In this, the models were started from a stable SOX9+ state and were switched to a RUNX2+ state, and vice versa. The in silico experiment predicted a transition from SOX9+ to RUNX2+ in the GP model with single addition of BMP or WNT, whereas in the AC model these factors caused no switch. The in silico experiments predicted a switch in the AC model with inhibition of IHH and simultaneous addition of high levels of either WNT or BMP (figure 2).In addition, we performed in silico double knockout and overexpression of all nodes in the network to predict which signals could interfere with OA development and progression. This resulted in hundreds of possible targets that are currently being investigated further. These experiments provide potential therapeutic clues for treatment of OA.

Conclusions: ECHO was used to mimic biological scenarios during chondrocyte development. We obtained insight into healthy chondrocyte development and OA development. Perturbation of single or double extracellular ligands cause a switch in cell fate, with BMP, WNT and IHH playing important roles. In addition, ECHO was used to identify potential therapeutic targets for OA treatment.
Original languageEnglish
PagesS176-S177
Number of pages1
DOIs
StatePublished - Apr 2016
Event2016 OARSI World Congress on Osteoarthrtis - Amsterdam, Netherlands

Conference

Conference2016 OARSI World Congress on Osteoarthrtis
CountryNetherlands
CityAmsterdam
Period31/03/163/04/16

Fingerprint

Chondrocytes
Computer Simulation
Cartilage Diseases
Ligands
Parathyroid Hormone-Related Protein
Growth Plate
Mesenchymal Stromal Cells
Osteoarthritis
Transforming Growth Factor beta
Hypertrophy
Cartilage
Signal Transduction
Intercellular Signaling Peptides and Proteins
Proteins
Homeostasis
Phosphotransferases

Keywords

  • Signaling pathways
  • IR-100418
  • EWI-26956
  • dynamic modeling
  • METIS-316899
  • Osteoarthritis
  • Timed Automata

Cite this

Schivo, S., Scholma, J., Huang, X., Huang, X., Zhong, L., Zhong, L., ... Post, J. N. (2016). An ECHO in biology II: Insights in chondrocyte cell fate. S176-S177. Abstract from 2016 OARSI World Congress on Osteoarthrtis, Amsterdam, Netherlands.DOI: 10.1016/j.joca.2016.01.347

Schivo, Stefano; Scholma, Jetse; Huang, X; Huang, Xiaobin; Zhong, L.; Zhong, Leilei; van de Pol, Jan Cornelis; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; Post, Janine Nicole / An ECHO in biology II: Insights in chondrocyte cell fate.

2016. S176-S177 Abstract from 2016 OARSI World Congress on Osteoarthrtis, Amsterdam, Netherlands.

Research output: Other research outputAbstract

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title = "An ECHO in biology II: Insights in chondrocyte cell fate",
abstract = "Purpose: An intricate network of regulatory processes determines the chondrocyte cell fate during development and maintains tissue homeostasis. In the event of a disease such as OA, the regulatory network is critically compromised. To cure the disease, we need to restore the regulatory processes to their original state. However, because of the inherent complexity of regulatory networks, they cannot be efficiently analyzed and understood without computational assistance. To obtain insight into the function of such complex networks we developed a dynamic computational model of chondrocytes, the Executable CHOndrocyte or ECHO. In ECHO cell fates corresponding to osteoarthritis as well as healthy chondrocytes can be investigated. We used ECHO to predict potential targets for switching from an OA-like chondrocyte to a healthy articular chondrocyte.Methods: We generated a computational model of growth plate chondrocytes (GP model) and a model of articular chondrocytes (AC model) In each model it is possible to set the activity of each of the proteins in the network at a level between 0 and 100 in increments of, for example, 1 or 10. It is also possible to randomly initialize the activities of proteins, or use a combination of random and set initializations. In silico experiments can then be carried out by simulating the evolution of the modelled regulatory network over time. We used ECHO to obtain insight into cross talk of 7 signal transduction pathways important for chondrocyte development and cartilage maintenance: IGF, PTHrP, BMP, FGF, TGFbeta, WNT, IHH. ECHO consists of a network of 123 intracellular signaling molecules (kinases) with 354 interactions. The network faithfully resembles current status of literature. RUNX2+ is the readout for hypertrophy and OA, and SOX9+ the readout of healthy articular chondrocytes. qPCR experiments on human mesenchymal stem cells (hMSCs) and human articular chondrocytes (hACs) were used to validate the model.Results: Using ECHO we analyzed the most influential pathways, and performed in silico experiments to obtain insight into the molecular mechanisms of cartilage development and disease. For example, we investigated the cell’s response to addition or inhibition of single (Figure 1), or combinations of growth factors or cytokines. Both the GP and AC models showed a dose-dependent response to (combinations of) external stimuli. qPCR validated this dose-dependency in MSC and chondrocytes.We then investigated switching cell state through perturbations of extra-cellular ligands. In this, the models were started from a stable SOX9+ state and were switched to a RUNX2+ state, and vice versa. The in silico experiment predicted a transition from SOX9+ to RUNX2+ in the GP model with single addition of BMP or WNT, whereas in the AC model these factors caused no switch. The in silico experiments predicted a switch in the AC model with inhibition of IHH and simultaneous addition of high levels of either WNT or BMP (figure 2).In addition, we performed in silico double knockout and overexpression of all nodes in the network to predict which signals could interfere with OA development and progression. This resulted in hundreds of possible targets that are currently being investigated further. These experiments provide potential therapeutic clues for treatment of OA.Conclusions: ECHO was used to mimic biological scenarios during chondrocyte development. We obtained insight into healthy chondrocyte development and OA development. Perturbation of single or double extracellular ligands cause a switch in cell fate, with BMP, WNT and IHH playing important roles. In addition, ECHO was used to identify potential therapeutic targets for OA treatment.",
keywords = "Signaling pathways, IR-100418, EWI-26956, dynamic modeling, METIS-316899, Osteoarthritis, Timed Automata",
author = "Stefano Schivo and Jetse Scholma and X Huang and Xiaobin Huang and L. Zhong and Leilei Zhong and {van de Pol}, {Jan Cornelis} and Karperien, {Hermanus Bernardus Johannes} and Romanus Langerak and Post, {Janine Nicole}",
note = "eemcs-eprint-26956",
year = "2016",
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doi = "10.1016/j.joca.2016.01.347",
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}

Schivo, S, Scholma, J, Huang, X, Huang, X, Zhong, L, Zhong, L, van de Pol, JC, Karperien, HBJ, Langerak, R & Post, JN 2016, 'An ECHO in biology II: Insights in chondrocyte cell fate' 2016 OARSI World Congress on Osteoarthrtis, Amsterdam, Netherlands, 31/03/16 - 3/04/16, pp. S176-S177. DOI: 10.1016/j.joca.2016.01.347

An ECHO in biology II: Insights in chondrocyte cell fate. / Schivo, Stefano; Scholma, Jetse; Huang, X; Huang, Xiaobin; Zhong, L.; Zhong, Leilei; van de Pol, Jan Cornelis; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; Post, Janine Nicole.

2016. S176-S177 Abstract from 2016 OARSI World Congress on Osteoarthrtis, Amsterdam, Netherlands.

Research output: Other research outputAbstract

TY - CONF

T1 - An ECHO in biology II: Insights in chondrocyte cell fate

AU - Schivo,Stefano

AU - Scholma,Jetse

AU - Huang,X

AU - Huang,Xiaobin

AU - Zhong,L.

AU - Zhong,Leilei

AU - van de Pol,Jan Cornelis

AU - Karperien,Hermanus Bernardus Johannes

AU - Langerak,Romanus

AU - Post,Janine Nicole

N1 - eemcs-eprint-26956

PY - 2016/4

Y1 - 2016/4

N2 - Purpose: An intricate network of regulatory processes determines the chondrocyte cell fate during development and maintains tissue homeostasis. In the event of a disease such as OA, the regulatory network is critically compromised. To cure the disease, we need to restore the regulatory processes to their original state. However, because of the inherent complexity of regulatory networks, they cannot be efficiently analyzed and understood without computational assistance. To obtain insight into the function of such complex networks we developed a dynamic computational model of chondrocytes, the Executable CHOndrocyte or ECHO. In ECHO cell fates corresponding to osteoarthritis as well as healthy chondrocytes can be investigated. We used ECHO to predict potential targets for switching from an OA-like chondrocyte to a healthy articular chondrocyte.Methods: We generated a computational model of growth plate chondrocytes (GP model) and a model of articular chondrocytes (AC model) In each model it is possible to set the activity of each of the proteins in the network at a level between 0 and 100 in increments of, for example, 1 or 10. It is also possible to randomly initialize the activities of proteins, or use a combination of random and set initializations. In silico experiments can then be carried out by simulating the evolution of the modelled regulatory network over time. We used ECHO to obtain insight into cross talk of 7 signal transduction pathways important for chondrocyte development and cartilage maintenance: IGF, PTHrP, BMP, FGF, TGFbeta, WNT, IHH. ECHO consists of a network of 123 intracellular signaling molecules (kinases) with 354 interactions. The network faithfully resembles current status of literature. RUNX2+ is the readout for hypertrophy and OA, and SOX9+ the readout of healthy articular chondrocytes. qPCR experiments on human mesenchymal stem cells (hMSCs) and human articular chondrocytes (hACs) were used to validate the model.Results: Using ECHO we analyzed the most influential pathways, and performed in silico experiments to obtain insight into the molecular mechanisms of cartilage development and disease. For example, we investigated the cell’s response to addition or inhibition of single (Figure 1), or combinations of growth factors or cytokines. Both the GP and AC models showed a dose-dependent response to (combinations of) external stimuli. qPCR validated this dose-dependency in MSC and chondrocytes.We then investigated switching cell state through perturbations of extra-cellular ligands. In this, the models were started from a stable SOX9+ state and were switched to a RUNX2+ state, and vice versa. The in silico experiment predicted a transition from SOX9+ to RUNX2+ in the GP model with single addition of BMP or WNT, whereas in the AC model these factors caused no switch. The in silico experiments predicted a switch in the AC model with inhibition of IHH and simultaneous addition of high levels of either WNT or BMP (figure 2).In addition, we performed in silico double knockout and overexpression of all nodes in the network to predict which signals could interfere with OA development and progression. This resulted in hundreds of possible targets that are currently being investigated further. These experiments provide potential therapeutic clues for treatment of OA.Conclusions: ECHO was used to mimic biological scenarios during chondrocyte development. We obtained insight into healthy chondrocyte development and OA development. Perturbation of single or double extracellular ligands cause a switch in cell fate, with BMP, WNT and IHH playing important roles. In addition, ECHO was used to identify potential therapeutic targets for OA treatment.

AB - Purpose: An intricate network of regulatory processes determines the chondrocyte cell fate during development and maintains tissue homeostasis. In the event of a disease such as OA, the regulatory network is critically compromised. To cure the disease, we need to restore the regulatory processes to their original state. However, because of the inherent complexity of regulatory networks, they cannot be efficiently analyzed and understood without computational assistance. To obtain insight into the function of such complex networks we developed a dynamic computational model of chondrocytes, the Executable CHOndrocyte or ECHO. In ECHO cell fates corresponding to osteoarthritis as well as healthy chondrocytes can be investigated. We used ECHO to predict potential targets for switching from an OA-like chondrocyte to a healthy articular chondrocyte.Methods: We generated a computational model of growth plate chondrocytes (GP model) and a model of articular chondrocytes (AC model) In each model it is possible to set the activity of each of the proteins in the network at a level between 0 and 100 in increments of, for example, 1 or 10. It is also possible to randomly initialize the activities of proteins, or use a combination of random and set initializations. In silico experiments can then be carried out by simulating the evolution of the modelled regulatory network over time. We used ECHO to obtain insight into cross talk of 7 signal transduction pathways important for chondrocyte development and cartilage maintenance: IGF, PTHrP, BMP, FGF, TGFbeta, WNT, IHH. ECHO consists of a network of 123 intracellular signaling molecules (kinases) with 354 interactions. The network faithfully resembles current status of literature. RUNX2+ is the readout for hypertrophy and OA, and SOX9+ the readout of healthy articular chondrocytes. qPCR experiments on human mesenchymal stem cells (hMSCs) and human articular chondrocytes (hACs) were used to validate the model.Results: Using ECHO we analyzed the most influential pathways, and performed in silico experiments to obtain insight into the molecular mechanisms of cartilage development and disease. For example, we investigated the cell’s response to addition or inhibition of single (Figure 1), or combinations of growth factors or cytokines. Both the GP and AC models showed a dose-dependent response to (combinations of) external stimuli. qPCR validated this dose-dependency in MSC and chondrocytes.We then investigated switching cell state through perturbations of extra-cellular ligands. In this, the models were started from a stable SOX9+ state and were switched to a RUNX2+ state, and vice versa. The in silico experiment predicted a transition from SOX9+ to RUNX2+ in the GP model with single addition of BMP or WNT, whereas in the AC model these factors caused no switch. The in silico experiments predicted a switch in the AC model with inhibition of IHH and simultaneous addition of high levels of either WNT or BMP (figure 2).In addition, we performed in silico double knockout and overexpression of all nodes in the network to predict which signals could interfere with OA development and progression. This resulted in hundreds of possible targets that are currently being investigated further. These experiments provide potential therapeutic clues for treatment of OA.Conclusions: ECHO was used to mimic biological scenarios during chondrocyte development. We obtained insight into healthy chondrocyte development and OA development. Perturbation of single or double extracellular ligands cause a switch in cell fate, with BMP, WNT and IHH playing important roles. In addition, ECHO was used to identify potential therapeutic targets for OA treatment.

KW - Signaling pathways

KW - IR-100418

KW - EWI-26956

KW - dynamic modeling

KW - METIS-316899

KW - Osteoarthritis

KW - Timed Automata

U2 - 10.1016/j.joca.2016.01.347

DO - 10.1016/j.joca.2016.01.347

M3 - Abstract

SP - S176-S177

ER -

Schivo S, Scholma J, Huang X, Huang X, Zhong L, Zhong L et al. An ECHO in biology II: Insights in chondrocyte cell fate. 2016. Abstract from 2016 OARSI World Congress on Osteoarthrtis, Amsterdam, Netherlands. Available from, DOI: 10.1016/j.joca.2016.01.347