Summary: Bacteria display various shapes and rely on complex spatial organization of their intracellular components for many cellular processes. This organization changes in response to internal and external cues. Quantitative, unbiased study of these spatio‐temporal dynamics requires automated image analysis of large microscopy datasets. We have therefore developed MicrobeTracker, a versatile and high‐throughput image analysis program that outlines and segments cells with subpixel precision, even in crowded images and mini‐colonies, enabling cell lineage tracking. MicrobeTracker comes with an integrated accessory tool, SpotFinder, which precisely tracks foci of fluorescently labelled molecules inside cells. Using MicrobeTracker, we discover that the dynamics of the extensively studied Escherichia coli Min oscillator depends on Min protein concentration, unveiling critical limitations in robustness within the oscillator. We also find that the fraction of MinD proteins oscillating increases with cell length, indicating that the oscillator has evolved to be most effective when cells attain an appropriate length. MicrobeTracker was also used to uncover novel aspects of morphogenesis and cell cycle regulation in Caulobacter crescentus. By tracking filamentous cells, we show that the chromosomal origin at the old‐pole is responsible for most replication/separation events while the others remain largely silent despite contiguous cytoplasm. This surprising position‐dependent silencing is regulated by division.

Summary: With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re‐emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single‐cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand‐alone, open‐source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non‐diffraction‐limited fluorescence signals and is scalable for high‐throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post‐processing analysis, makes the software broadly accessible to users irrespective of their computational skills.

Eukaryotic cells spatially organize mRNA processes such as translation and mRNA decay. Much less is clear in bacterial cells where the spatial distribution of mature mRNA remains ambiguous. Using a sensitive method based on quantitative fluorescence in situ hybridization, we show here that in Caulobacter crescentus and Escherichia coli, chromosomally expressed mRNAs largely display limited dispersion from their site of transcription during their lifetime. We estimate apparent diffusion coefficients at least two orders of magnitude lower than expected for freely diffusing mRNA, and provide evidence in C. crescentus that this mRNA localization restricts ribosomal mobility. Furthermore, C. crescentus RNase E appears associated with the DNA independently of its mRNA substrates. Collectively, our findings show that bacteria can spatially organize translation and, potentially, mRNA decay by using the chromosome layout as a template. This chromosome-centric organization has important implications for cellular physiology and for our understanding of gene expression in bacteria.