Escherichia coli Chromosomal Loci Segregate from Midcell with Universal Dynamics

Abstract

The structure of the Escherichia coli chromosome is inherently dynamic over the duration of the cell cycle. Genetic loci undergo both stochastic motion around their initial positions and directed motion to opposite poles of the rod-shaped cell during segregation. We developed a quantitative method to characterize cell-cycle dynamics of the E. coli chromosome to probe the chromosomal steady-state mobility and segregation process. By tracking fluorescently labeled chromosomal loci in thousands of cells throughout the entire cell cycle, our method allows for the statistical analysis of locus position and motion, the step-size distribution for movement during segregation, and the locus drift velocity. The robust statistics of our detailed analysis of the wild-type E. coli nucleoid allow us to observe loci moving toward midcell before segregation occurs, consistent with a replication factory model. Then, as segregation initiates, we perform a detailed characterization of the average segregation velocity of loci. Contrary to origin-centric models of segregation, which predict distinct dynamics for oriC-proximal versus oriC-distal loci, we find that the dynamics of loci were universal and independent of genetic position.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells

“…SuperSegger is a powerful automated image processing and analysis package, well suited for high-throughput time-lapse fluorescence microscopy of cells (LeRoux et al, 2012;O'Connor et al, 2012;Kuwada et al, 2013;Russell et al, 2013;Garmendia-Torres et al, 2014;Javer et al, 2014;Kuwada et al, 2015a,b;Lampo et al, 2015;LeRoux et al, 2015a;Stylianidou et al, 2015;Cass et al, 2016). It provides reliable and flexible segmentation which can be trained to optimize performance in a wide variety of experimental contexts.…”

“…Panel B : Cell towers (example of mini‐F plasmids labeled with mCherry‐TetR and ParA‐GFP (ATPase) [Ietswaart et al ., )]. Panel C : Kymographs (example shows of parS cassette inserted at oriC and labeled with GFP‐ParB (Cass et al ., ) and cell movies (Movie S1). Frame files contain the data from a single field of view at a time point.…”

“…In this article, we present SuperSegger , an automated MATLAB‐based image processing and analysis package. To date, we have successfully applied our package to a number of problems in the cell biology of bacterial cells, including a genome‐scale characterization of protein localization dynamics in Escherichia coli throughout the cell cycle (Kuwada et al ., , ), detailed analysis of the function of the Type VI Secretion System in Pseudomonas aeruginosa (LeRoux et al ., ; Russell et al ., ; LeRoux et al ., ), chromosome segregation in E. coli (Kuwada et al ., ; Cass et al ., ) as well as a number of other applications (O'Connor et al ., ; Stylianidou et al ., ). SuperSegger is particularly well suited for high‐throughput analysis of cell‐cycle dynamics of proteins and complexes by time‐lapse fluorescence microscopy in single bacterial cells.…”

Probing bacterial cell biology using image cytometry

“…We have already used this method, without detailed description, in a number of papers (Wiggins et al ., ; LeRoux et al ., ; Kuwada et al ., ; Stylianidou et al ., ; Kuwada et al ., ; LeRoux et al ., ; Kuwada et al ., ; Cass et al ., ; Stylianidou et al ., ), and the software is available for download from the Wiggins Lab website (http://mtshasta.phys.washington.edu/website/ssodownload.php). The purpose of the current report is to describe the method and to demonstrate its potential.…”

“…Quantitative fluorescence imaging has become an important tool for the study of the bacterial cell biology (van Teeffelen et al, 2012). Most cellular processes, from chromosome segregation to replication, are stochastic in nature and exhibit significant cell-to-cell variation (Kuwada et al, 2013;Kuwada et al, 2015a;Cass et al, 2016). This variation makes the quantitative statistical analysis of a significant number of cells essential (Kuwada et al, 2015a).…”