Additional file 1: of Re-using biological devices: a model-aided analysis of interconnected transcriptional cascades designed from the bottom-up
Creators: name: Pasotti, Lorenzo
name: Bellato, Massimo
name: Casanova, Michela
name: Zucca, Susanna
name: Angelis, Maria Cusella De
name: Magni, Paolo
Publisher: name: figshare
Year: 2017
Subjects: subject: Biophysics
subject: Biochemistry
subject: Space Science
subject: Microbiology
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: Genetics
subject: Molecular Biology
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: FOS: Earth and related environmental sciences
subject: Developmental Biology
subject: Hematology
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: FOS: Health sciences

description: Supplementary Notes. Supplementary analysis of circuits data. Supplementary Figures. Figure S1. RFP output data for the cascade circuits tested in this work (training and test set) as a function of HSL concentration. Figure S2. Growth rate data for the cascade circuits tested in this work (training and test set) as a function of HSL concentration. Figure S3. GFP output data for the cascade circuits with Monitor cassette tested in this work (training and test set) as a function of HSL concentration. Figure S4. Growth rate (A) and RFP (B) comparison plots between strains without and with Monitor cassette at all the tested HSL concentrations for all the circuits (training and test set). Figure S5. Correlation between GFP and growth rate in all the strains (training and test set) with the Monitor cassette at all the tested HSL concentrations. Figure S6. Correlation between GFP and growth rate for each strain with the Monitor cassette at all the tested HSL concentrations. Figure S7. Correlation between GFP and RFP for each strain with the Monitor cassette at all the tested HSL concentrations. Figure S8. NBM fitting of the measured HSL-dependent output in all the training set circuits without Monitor cassette. Figure S9. NBM fitting of the two NOT gate characteristics as a function of the predicted per cell concentration of the TetR or LacI repressor. Figure S10. Univariate sensitivity analysis of the NBM by applying a variation on the δ parameter of the Hill functions. Figure S11. Univariate sensitivity analysis of the NBM by applying a variation on the α parameter of the Hill functions. Figure S12. Univariate sensitivity analysis of the NBM by applying a variation on the K parameter of the Hill functions. Figure S13. Univariate sensitivity analysis of the NBM by applying a variation on the η parameter of the Hill functions. Figure S14. Evolutionary stability of the X1TLr and XrepTLr circuits. Figure S15. Simulation of X1TLr and XrepTLr with the NBM for different values of γtet and γlac parameters. Figure S16. Fitting and prediction results for the NBM learned and simulated against RFP data of the circuits with the Monitor cassette. Figure S17. BM fitting of the measured HSL-dependent RFP output in all the training set circuits with Monitor cassette. Figure S18. BM fitting of the measured HSL-dependent GFP output in all the training set circuits with Monitor cassette. Figure S19. Results of fitting using all the available data (training and test set) using NBM and BM: RFP data. Figure S20. Results of fitting using all the available data (training and test set) using BM: GFP data. Figure S21. OD600, raw GFP and raw RFP values measured in culture, supernatant and pellet of three strains. Figure S22. Raw GFP autofluorescence depends on OD600 and also cell growth rate. Supplementary Tables. Table S1. Parts used in this study. Table S2. Statistics on circuits bearing the burden monitor. (PDF 2853 kb)