DOI: 10.7488/ds/7476
title: Environmental conditions define the energetics of bacterial dormancy and its antibiotic susceptibility

description: Bacterial cells that stop growing but maintain viability and the capability to regrow are termed dormant and have been shown to transiently tolerate high concentrations of antimicrobials. Links between tolerance and cellular energetics as a possible explanation for the tolerance, have been investigated and have produced mixed and seemingly contradictory results. Because dormancy merely indicates growth arrest, which can be induced by various stimuli, we hypothesise that dormant cells may exist in a range of energetic states that depend on the environment. To energetically characterise different dormancies, we first induce them in a way that results in dormant populations and subsequently measured both of their main energy sources, the PMF magnitude and the concentration of ATP. We find that different types of dormancy exhibit characteristic energetic profiles that vary in level and dynamics. The energetic makeup was associated with survival to some antibiotics, but not others. Our findings portray dormancy as a state that is rich in phenotypes with various stress survival capabilities. Because environmental conditions outside of the lab often halt or limit microbial growth, a typologisation of dormant states may yield relevant insights on the survival and evolutionary strategies of these organisms. This is the supporting data for the upcoming publication Leonardo Mancini, Teuta Pilizota (pre-accepted), "Environmental conditions define the energetics of bacterial dormancy and its antibiotic susceptibility", Biophysical journal.
description: The dataset provides optical density readings, bacterial flagellar motor speed readings, microscopy images, and data points from which the main figures were generated, supporting the manuscript: "Environmental conditions define the energetics of bacterial dormancy and its antimicrobial susceptibility". The archive contains: Folder 2A contains images pertaining to Fig. 2A of the manuscript. The images are organised according the legend from Fig. 2A. Each legend item is then organised in subfolders grouped per experimental repeat. Each experimental repeat contains contains a subfolder per experimental time point. Folder 3A contains images pertaining to Fig. 3A of the manuscript. Each subfolder corresponds to one label of the Figure's x axis. Each of these is then organised in subfolders, containing images from different fields of view (FOVs). Folder 3B contains images pertaining to Fig. 3B of the manuscript. Each subfolder contains a different experimental repeat as per the figure's legend. Each repeat contains a subfolder per condition (ATP concentration) containing microscopy images. Folder 3C contains images and bacterial flagellar motor speed measurements pertaining to Fig. 3C of the manuscript. The subfolders are organised per condition as explained by the figure's x axes. Each condition, in turn, contains subfolders with images concerning ATP or pH measurements or motor speed files and are named accordingly. The remaining data, is given in a .xlsx file where every spreadsheet corresponds to a figure subpanel. Rows and columns headers in accordance to axes labels and legends. The archive is accompanied by a readme.txt file reiterating this description.