Conclusions The LY333531 mouse method of growth curve synchronization proposed here provides a simple, inexpensive solution to integrate rich time-resolved data with endpoint measurements. Like other model-based PD-1/PD-L1 Inhibitor 3 data integration methods [42], our method aims at a major limitation in systems biology -the scarceness of high quality time-resolved quantitative data. In the specific case of P. aeruginosa,

this method can be used to validate and complement metabolic models. For example, the fluxes of secreted secondary metabolites measured for isogenic mutants can help further refine metabolic models from whole genome reconstruction [43, 44]. Beyond P. aeruginosa, growth curve synchronization can be a general method to help unravel regulation dynamics in biological systems. Additional files General comments In order to run the Matlab demonstration (AdditionalFile3.m) place the two. csv files (AdditionalFile1.csv and AdditionalFile2.csv) in the same folder. Inside of this latter folder both of the .m files should be saved. The matlab code was written for Matlab R2010a with the statistics and optimization toolboxes. Acknowledgements and funding The authors would like

to thank Justina Sanny for cloning the reporter fusion strains and comments on the manuscript. Additional thanks go to Vanni Bucci, Laura de Vargas Roditi, Will Chang and Alex Root for comments on the manuscript. This work was supported by a seed grant from the Lucille Castori Center for Microbes, Inflammation and Cancer. Electronic supplementary material Additional

file 1: Matlab-based growth curve synchronization algorithm. APR-246 in vitro This is the main algorithm for growth curve alignment. The script calls AdditionalFile4.m and uses functions from the statistics and optimization toolboxes. The program draws plots of the data before alignment, after alignment, a time series of rhamnolipid production and the time shift versus dilution, yielding the growth rate. (M 9 KB) Additional file 2: Matlab suite. AdditionalFile4.m is a Matlab file implementing a suite of functions for reading, processing and plotting growth curve data. (M 28 KB) Additional file 3: Raw Isoconazole data file for growth curve synchronization. This file contains the raw data from a typical growth curve synchronization experiment. In this document, all the data is included, started with the optical density measurement (called od600) and then the GFP measurement (called gfp). Time is given in seconds. The first 8 samples (A1 through H1) are the blank, the second set of eight (A2 through H2) are from the culture inoculated at 0.0025 OD600, etc. The ninth set of eight (A9 through H9) contain the last set of data, the last sets (A10 through H12) are empty wells. This is one of the files used by the Matlab algorithm (AdditionalFile3.m) in order to synchronize the growth curves. (CSV 271 KB) Additional file 4: Rhamnose quantification for different time points. This file contains an example of rhamnose quantification from the sulfuric acid anthrone assay.