Parameter inference of a basic p53 model using ABC

Transcription

1 Parameter inference of a basic p53 model using ABC Eszter Lakatos and Michael Barclay Group meeting 29 th October 2014 p53 - ABC II. Eszter 1 / 10

2 Background Study p53 reaction to cellular stress on single cell level Compare and model (stochastically) normal and drug-treated cells MCF-7 cells human breast cancer cell line BE cells bigger cells, faster growth Actinomycin D polypeptide antibiotic with anti-cancer activity transcriptional inhibitor low concentration induces a p53-dependent apoptosis p53 - ABC II. Eszter 2 / 10

3 Experimental results MCF7 cells (n = 45) 16 BE cells (n = 51) x x nM ActinomycinD (n = 69) 20 40nM ActinomycinD (n = 58) 15 80nM ActinomycinD (n = 65) x x x 10 4 Hypothesis: drug affects p53 degradation p53 - ABC II. Eszter 3 / 10

4 Model ṁ = k 1 k 2 m ṗ = k 3 m k 4 p k 1 - transcription k 2 - mrna degr. k 3 - translation k 4 - protein degr. p53 - ABC II. Eszter 4 / 10

5 Model ṁ = k 1 k 2 m ṗ = k 3 m k 4 p k 1 - transcription k 2 - mrna degr. k 3 - translation k 4 - protein degr. p53 - ABC II. Eszter 4 / 10

6 Combined model of different cell populations MCF7: BE: m 1 = k 1 k 2 m 1 p 1 = k 3 m 1 k 4 p 1 m 2 = k 1 s k 2 sm 2 p 2 = k 3 sm 2 k 4 sk 5 p 2 k 1 - transcription s - scaling factor k 2 - mrna degr. k 5 - modifier k 3 - translation k 4 - protein degr. Hypothesis: k 5 << 1 p53 - ABC II. Eszter 5 / 10

7 Combined model of different cell populations 8nM ActD: 40nM ActD: 80nM ActD: m 1 = k 1 k 2 m 1 m 2 = k 1 k 2 m 2 m 3 = k 1 k 2 m 3 p 1 = k 3 m 1 k 4 p 1 p 2 = k 3 m 2 k 5 p 2 p 3 = k 3 m 3 k 6 p 3 k 1 - transcription k 5 - protein degr. k 6 - protein degr. k 2 - mrna degr. k 3 - translation k 4 - protein degr. Hypothesis: k 6 < k 5 < k 4 p53 - ABC II. Eszter 5 / 10

8 Inference using ABC Algorithm Sample parameters from (prior) distribution Simulate each particle n times: SDE Compare experimental and simulated populations Accept particle if distance < ɛ Iterate p53 - ABC II. Eszter 6 / 10

9 Inference using ABC Algorithm Sample parameters from (prior) distribution Simulate each particle n times: SDE Compare experimental and simulated populations Accept particle if distance < ɛ Iterate Conclusions from the first months: Kolmogorov-Smirnov distance Non-identifiability Rescale parameters by setting k 2 = 1 Check the limitations with simulated experimental data Focus on base MCF7 and ActD-treated cells p53 - ABC II. Eszter 6 / 10

10 Results I. - Identifiability Populations (n = 60) simulated with the same parameters sim. experimental simulation0 simulation1 p53 - ABC II. Eszter 7 / 10

11 Results I. - Identifiability p 1 = 0.2, p 2 = 1e5, p 3 = 10 p53 - ABC II. Eszter 7 / 10

12 Results I. - Identifiability p 1 = 0.2, p 2 = 1e5, p 3 = 10, p 4 = 0.01 p53 - ABC II. Eszter 7 / 10

13 Results I. - Identifiability p 1 = 0.2, p 2 = 1e5, p 3 = 10, p 4 = 5, p 5 = 2.5 p53 - ABC II. Eszter 7 / 10

14 Results I. - Identifiability p 1 = 0.2, p 2 = 1e5, p 3 = 10, p 4 = 5, p 5 = 2.5 p53 - ABC II. Eszter 7 / 10

15 Combined model of different cell populations MCF7: BE: m 1 = k 1 k 2 m 1 p 1 = k 3 m 1 k 4 p 1 m 2 = k 1 s k 2 sm 2 p 2 = k 3 sm 2 k 4 sk 5 p 2 k 1 - transcription s - scaling factor k 2 - mrna degr. k 5 - modifier k 3 - translation k 4 - protein degr. Hypothesis: k 5 << 1 p53 - ABC II. Eszter 8 / 10

16 Combined model of different cell populations 8nM ActD: 40nM ActD: 80nM ActD: m 1 = k 1 k 2 m 1 m 2 = k 1 k 2 m 2 m 3 = k 1 k 2 m 3 p 1 = k 3 m 1 k 4 p 1 p 2 = k 3 m 2 k 5 p 2 p 3 = k 3 m 3 k 6 p 3 k 1 - transcription k 5 - protein degr. k 6 - protein degr. k 2 - mrna degr. k 3 - translation k 4 - protein degr. Hypothesis: k 6 < k 5 < k 4 p53 - ABC II. Eszter 8 / 10

17 Results II. - Real data Combined model of MCF7 and BE cells p53 - ABC II. Eszter 9 / 10

18 Results II. - Real data Combined model of MCF7 and BE cells simulation1 simulation2 experimental p53 - ABC II. Eszter 9 / 10

19 Results II. - Real data Combined model of 3 doses of ActinomycinD treatment p53 - ABC II. Eszter 9 / 10

20 Results II. - Real data Combined model of 3 doses of ActinomycinD treatment simulation1 simulation2 experimental p53 - ABC II. Eszter 9 / 10

21 Results II. - Real data Combined models of 3 doses of ActinomycinD treatment Model 1: ActD affects protein degradation Model 2: ActD affects transcription Model 3: ActD affects translation p53 - ABC II. Eszter 9 / 10

22 Results II. - Real data Combined models of 3 doses of ActinomycinD treatment simulation13 simulation83 simulation98 experimental p53 - ABC II. Eszter 9 / 10

23 Plans, problems, questions More data (faster set-up) Fluorescent data from MCF7 and BE cells Both p53 and Mdm2 labelling Low molecular numbers of protein are not measured reliably E.g. in the MCF7 cell line, about 10 cells were thrown out Can be considered in distance Two populations of cells Pin down exact numbers p53 - ABC II. Eszter 10 / 10