The stochasticity of chromosome organization was investigated by fluorescently labeling genetic loci in live Escherichia coli cells. In spite of the common assumption that the chromosome is well modeled by an unstructured polymer, measurements of the locus distributions reveal that the E. coli chromosome is precisely organized into a nucleoid filament with a linear order. Loci in the body of the nucleoid show a precision of positioning within the cell of better than 10% of the cell length. The precision of interlocus distance of genomically-proximate loci was better than 4% of the cell length. The measured dependence of the precision of interlocus distance on genomic distance singles out intranucleoid interactions as the mechanism responsible for chromosome organization. From the magnitude of the variance, we infer the existence of an as-yet uncharacterized higher-order DNA organization in bacteria. We demonstrate that both the stochastic and average structure of the nucleoid is captured by a fluctuating elastic filament model. chromosome segregation | chromosome structure | nucleoid structure | polymer physics P rokaryotic chromosomes are organized into a compact DNA-protein complex called the nucleoid (1, 2). The physical structure of chromosomes has functional consequences, for example it affects gene regulation from the simplest prokaryotes (1) to multicellular organisms (3). Nucleoid organization and condensation also appear to play a central role in chromosome segregation: Mutants with defective chromosome segregation are typically accompanied by abnormal nucleoid organization or condensation (2). Although a significant number of such genes have been identified by genetic screens, the mechanism by which these molecular players effect the cellular-scale nucleoid structure is not yet understood (2). Similarly, the mechanism by which prokaryotic chromosomes are segregated is still hotly debated (2, 4, 5). The apparent dispensability of a mitotic-spindle-like mechanism in chromosome segregation in Escherichia coli (2, 4) has led to speculation that nucleoid organization and segregation may be the result of several redundant mechanisms, including polymer physics-embodied by the combined effects of entropy, confinement, and excluded volume-rather than resulting from the action of dedicated cellular machinery alone (2, 6, 7). This paper complements earlier work by focusing on the measurement and theoretical interpretation of two classes of statistical measures of chromosome organization: (i) the distributions of the positions of individual loci within the cell; and (ii) the distributions of displacements between pairs of genetic loci. We argue that the measurement and analysis of these distributions sheds light on the mechanisms of chromosomal positioning that have not been revealed in earlier measurements. The cellular-scale structure of the circular Caulobacter crescentus chromosome has already been shown to be linearly organized between replication cycles, with the origin of replication at one pole and the ter...

The mechanism responsible for the accurate partitioning of newly replicated Escherichia coli chromosomes into daughter cells remains a mystery. In this article, we use automated cell cycle imaging to quantitatively analyse the cell cycle dynamics of the origin of replication (oriC) in hundreds of cells. We exploit the natural stochastic fluctuations of the chromosome structure to map both the spatial and temporal dependence of the motional bias segregating the chromosomes. The observed map is most consistent with force generation by an active mechanism, but one that generates much smaller forces than canonical molecular motors, including those driving eukaryotic chromosome segregation.

Explaining the diversity and complexity of protein localization is essential to fully understand cellular architecture. Here we present cytoself, a deep-learning approach for fully self-supervised protein localization profiling and clustering. Cytoself leverages a self-supervised training scheme that does not require preexisting knowledge, categories or annotations. Training cytoself on images of 1,311 endogenously labeled proteins from the OpenCell database reveals a highly resolved protein localization atlas that recapitulates major scales of cellular organization, from coarse classes, such as nuclear and cytoplasmic, to the subtle localization signatures of individual protein complexes. We quantitatively validate cytoself’s ability to cluster proteins into organelles and protein complexes, showing that cytoself outperforms previous self-supervised approaches. Moreover, to better understand the inner workings of our model, we dissect the emergent features from which our clustering is derived, interpret them in the context of the fluorescence images, and analyze the performance contributions of each component of our approach.

We explore how ligand-receptor binding kinetics can be controlled by tethering the receptor to the end of a flexible polymer. The tether confines the diffusive motion of the receptor thus influencing the rate at which it captures ligands that are free in solution. We compute steady-state collision rates between ligand and receptor for this "tethered-capture" mechanism using a combination of analytic and numerical techniques. In doing so, we uncover a dimensionless control parameter, the "opacity," that determines under what conditions and to what extent a tether regulates the ligand-receptor collision rate. We compute the opacity for a number of different tethering scenarios that appear in biology and use these results to predict the affect of changing the length and flexibility of the tether on the rate at which ligands are captured from solution.