Introduction | Current metrics adopted in the clinical setting, such as the MIC, do not account for the time course of antimicrobial activity and are not sufficiently predictive of treatment efficacy [22,45 —47]. |
Supporting Information | (A,F) Time courses for populations with initial densities that are 10X and 100x smaller than the base model. |
Supporting Information | (A) Time course . |
Supporting Information | (F) Time course . |
Discovery of non-coding RNA genes active in the immediate-early response | A lower threshold was used for the initial data selection: A minimum sum of 3 TPM normalised by relative log expression (RLE) over the time course was used as a threshold to increase the number of time courses from the more conservative 10 TPM criteria used for protein coding genes. |
Discovery of non-coding RNA genes active in the immediate-early response | DNaseI hypersensitivity data for MCF7 cells [37, 38] were determined for 200 bp windows centered at the midpoint of each protein-coding and non-coding MCF7 time course CAGE cluster. |
Discovery of non-coding RNA genes active in the immediate-early response | Clusters associated with transcription factors were also in more accessible regions (p = 0.018), but, surprisingly, clusters assigned to known IEGs or nucleotide binding genes did not differ significantly from the reference set in either MCF7 time course (p > 0.08 by Wilcoxon rank sum test). |
Kinetics and chromatin features underlying IEG induction | This pattern was less apparent in the MCF7-HRG cell line where the proportion of known IEGs found in an interval exceeded the overall average towards the end of the time course . |
Kinetics and chromatin features underlying IEG induction | The transcriptional repressor NAB2 peaked relatively late in both MCF7 time courses . |
Kinetics and chromatin features underlying IEG induction | Nucleotide binding genes found to peak within 240 min in both MCF7 time courses included the transcription factor RUNX1 and three IEGs: TRIB1, SIK1 and GEM. |
Results | Kinetic signatures serve as prototypical patterns reflecting changes in regulation, and are used here as a means to categorise time course responses for each transcript present. |
Results | CAGE clusters assigned to approximately 200 known IEGs showed significantly elevated expression at the start of the time course , hence the importance of including the p1 parameter in the kinetic signatures (see Fig 1B). |
Results | An example of fitting early peak and linear models to an EGR1 time course is presented in Fig 1C. |
Supporting Information | Time course of receptor number and IL-2 concentration at the cell surface, see Fig 3E and 3F. |
ln-silico Th cell culture exhibits localized paracrine lL-2 signaling | Analysis of the time course (Fig 3E) shows that all cells upregulate IL-2R levels in response to the increased IL-2 concentration in the first hours after antigenic stimulation and IL-2 secretion. |
ln-silico Th cell culture exhibits localized paracrine lL-2 signaling | Interestingly, the time courses of IL-2 concentrations at the surfaces of the cells show only small differences between IL-2Rhigh and IL-2R10W cells (Fig 3F): In the beginning, IL-2 equally rises near IL-2Rhigh and IL-2R10w cells (see Fig 3D), but as IL-2 depletion sets in, the cells that eventually become IL-2R10W cells receive slightly less IL-2. |