Genomewide phenotypic analysis of growth, cell morphogenesis, and cell cycle events in Escherichia coli

Abstract

Cell size, cell growth, and cell cycle events are necessarily intertwined to achieve robust bacterial replication. Yet, a comprehensive and integrated view of these fundamental processes is lacking. Here, we describe an image‐based quantitative screen of the single‐gene knockout collection of Escherichia coli and identify many new genes involved in cell morphogenesis, population growth, nucleoid (bulk chromosome) dynamics, and cell division. Functional analyses, together with high‐dimensional classification, unveil new associations of morphological and cell cycle phenotypes with specific functions and pathways. Additionally, correlation analysis across ~4,000 genetic perturbations shows that growth rate is surprisingly not predictive of cell size. Growth rate was also uncorrelated with the relative timings of nucleoid separation and cell constriction. Rather, our analysis identifies scaling relationships between cell size and nucleoid size and between nucleoid size and the relative timings of nucleoid separation and cell division. These connections suggest that the nucleoid links cell morphogenesis to the cell cycle.

Environmental pH impacts division assembly and cell size inEscherichia coli

“…An alkaline environment likely has the opposite effect—reducing affinity between divisome components and inhibiting FtsN recruitment. Significantly, pH impacts cell size independent of growth rate, contributing to a growing body of evidence suggesting that these parameters are independent [11,55,56].…”

Arrayed CRISPRi and Quantitative Imaging Describe the Morphotypic Landscape of Essential Mycobacterial Genes

“…Jacobs-Wagner and colleagues (Campos, Govers et al 2018). In particular, we adapted a 522 machine-learning based cleanup that leverages the power of MicrobeJ but adds a 523…”

“…To quantitate these observations, we adapted an approach developed for E. coli 213 (Campos, Govers et al 2018). Single-cell data were reduced to normalized, gene-level 214 descriptors of morphology.…”

“…We corrected for multiple testing using the Benjamini-Hochberg Procedure and 885 utilized a significance cut-off of p < 0.05. For display of data, we opted to replicate prior work 886 (Campos, Govers et al 2018) in displaying all genes found above or below the threshold. COG 887 categories that were enriched for a particular feature were highlighted to differentiate them 888 from the background.…”

“…A population of cells at a single timepoint contains a degree of temporal information, as the 931 population contains cells at different stages of the cell cycle (Campos, Govers et al 2018…”