Nucleoid-mediated positioning and transport in bacteria.

Precise management of the spatiotemporal position of subcellular components is critical to a number of essential processes in the bacterial cell. The bacterial nucleoid is a highly structured yet dynamic object that undergoes significant reorganization during the relatively short cell cycle, e.g. during gene expression, chromosome replication, and segregation. Although the nucleoid takes up a large fraction of the volume of the cell, the mobility of macromolecules within these dense regions is relatively high and recent results suggest that the nucleoid plays an integral role of dynamic localization in a host of seemingly disparate cellular processes. Here, we review a number of recent reports of nucleoid-mediated positioning and transport in the model bacteria Escherichia coli. These results viewed as a whole suggest that the dynamic, cellular-scale structure of the nucleoid may be a key driver of positioning and transport within the cell. This model of a global, default positioning and transport system may help resolve many unanswered questions about the mechanisms of partitioning and segregation in bacteria.

Probing bacterial cell biology using image cytometry.

Advances in automated fluorescence microscopy have made snapshot and time-lapse imaging of bacterial cells commonplace, yet fundamental challenges remain in analysis. The vast quantity of data collected in high-throughput experiments requires a fast and reliable automated method to analyze fluorescence intensity and localization, cell morphology and proliferation as well as other descriptors. Inspired by effective yet tractable methods of population-level analysis using flow cytometry, we have developed a framework and tools for facilitating analogous analyses in image cytometry. These tools can both visualize and gate (generate subpopulations) more than 70 cell descriptors, including cell size, age and fluorescence. The method is well suited to multi-well imaging, analysis of bacterial cultures with high cell density (thousands of cells per frame) and complete cell cycle imaging. We give a brief description of the analysis of four distinct applications to emphasize the broad applicability of the tool.

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

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution.

Escherichia coli Chromosomal Loci Segregate from Midcell with Universal Dynamics.

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.

High-throughput cell-cycle imaging opens new doors for discovery.

During the life of a cell, numerous essential cellular processes must be coordinated both spatially and temporally, from DNA replication and chromosome segregation to gene expression and cytokinesis. In order to analyze these inherently dynamic and cell-cycle-dependent processes, it is essential to observe the dynamic localization of the cellular machinery throughout the entire cell cycle. Although some coarse features of cell-cycle dynamics can be captured in snapshot imaging, where cellular size or morphology can be used as a proxy for cell-cycle phase, the inherently stochastic nature of ultrastructures in the cell makes the direct visualization of subcellular dynamics an essential tool to differentiate between structural differences that are the result of biologically relevant dynamics versus cell-to-cell variation. With these goals in mind, we have developed a unique high-throughput imaging approach, and have recently applied this to characterize the cell-cycle localization of nearly every protein in the bacterial cell (Kuwada in Mol Microbiol, 95(1), 64-79, 2015). This approach combines large-format sample preparation with automated image capture, processing, and analysis to quantitatively characterize proteome localization of tens of thousands of complete cell cycles.

Physical modeling of chromosome segregation in escherichia coli reveals impact of force and DNA relaxation.

The physical mechanism by which Escherichia coli segregates copies of its chromosome for partitioning into daughter cells is unknown, partly due to the difficulty in interpreting the complex dynamic behavior during segregation. Analysis of previous chromosome segregation measurements in E. coli demonstrates that the origin of replication exhibits processive motion with a mean displacement that scales as t(0.32). In this work, we develop a model for segregation of chromosomal DNA as a Rouse polymer in a viscoelastic medium with a force applied to a single monomer. Our model demonstrates that the observed power-law scaling of the mean displacement and the behavior of the velocity autocorrelation function is captured by accounting for the relaxation of the polymer chain and the viscoelastic environment. We show that the ratio of the mean displacement to the variance of the displacement during segregation events is a critical metric that eliminates the compounding effects of polymer and medium dynamics and provides the segregation force. We calculate the force of oriC segregation in E. coli to be ∼0.49 pN.

Genome-scale quantitative characterization of bacterial protein localization dynamics throughout the cell cycle.

Bacterial cells display both spatial and temporal organization, and this complex structure is known to play a central role in cellular function. Although nearly one-fifth of all proteins in Escherichia coli localize to specific subcellular locations, fundamental questions remain about how cellular-scale structure is encoded at the level of molecular-scale interactions. One significant limitation to our understanding is that the localization behavior of only a small subset of proteins has been characterized in detail. As an essential step toward a global model of protein localization in bacteria, we capture and quantitatively analyze spatial and temporal protein localization patterns throughout the cell cycle for nearly every protein in E. coli that exhibits nondiffuse localization. This genome-scale analysis reveals significant complexity in patterning, notably in the behavior of DNA-binding proteins. Complete cell-cycle imaging also facilitates analysis of protein partitioning to daughter cells at division, revealing a broad and robust assortment of asymmetric partitioning behaviors.

Cytoplasmic dynamics reveals two modes of nucleoid-dependent mobility.

It has been proposed that forces resulting from the physical exclusion of macromolecules from the bacterial nucleoid play a central role in organizing the bacterial cell, yet this proposal has not been quantitatively tested. To investigate this hypothesis, we mapped the generic motion of large protein complexes in the bacterial cytoplasm through quantitative analysis of thousands of complete cell-cycle trajectories of fluorescently tagged ectopic MS2-mRNA complexes. We find the motion of these complexes in the cytoplasm is strongly dependent on their spatial position along the long axis of the cell, and that their dynamics are consistent with a quantitative model that requires only nucleoid exclusion and membrane confinement. This analysis also reveals that the nucleoid increases the mobility of MS2-mRNA complexes, resulting in a fourfold increase in diffusion coefficients between regions of the lowest and highest nucleoid density. These data provide strong quantitative support for two modes of nucleoid action: the widely accepted mechanism of nucleoid exclusion in organizing the cell and a newly proposed mode, in which the nucleoid facilitates rapid motion throughout the cytoplasm.

Unidirectional P-body transport during the yeast cell cycle.

P-bodies belong to a large family of RNA granules that are associated with post-transcriptional gene regulation, conserved from yeast to mammals, and influence biological processes ranging from germ cell development to neuronal plasticity. RNA granules can also transport RNAs to specific locations. Germ granules transport maternal RNAs to the embryo, and neuronal granules transport RNAs long distances to the synaptic dendrites. Here we combine microfluidic-based fluorescent microscopy of single cells and automated image analysis to follow p-body dynamics during cell division in yeast. Our results demonstrate that these highly dynamic granules undergo a unidirectional transport from the mother to the daughter cell during mitosis as well as a constrained "hovering" near the bud site half an hour before the bud is observable. Both behaviors are dependent on the Myo4p/She2p RNA transport machinery. Furthermore, single cell analysis of cell size suggests that PBs play an important role in daughter cell growth under nutrient limiting conditions.

Persistent super-diffusive motion of Escherichia coli chromosomal loci.

The physical nature of the bacterial chromosome has important implications for its function. Using high-resolution dynamic tracking, we observe the existence of rare but ubiquitous 'rapid movements' of chromosomal loci exhibiting near-ballistic dynamics. This suggests that these movements are either driven by an active machinery or part of stress-relaxation mechanisms. Comparison with a null physical model for subdiffusive chromosomal dynamics shows that rapid movements are excursions from a basal subdiffusive dynamics, likely due to driven and/or stress-relaxation motion. Additionally, rapid movements are in some cases coupled with known transitions of chromosomal segregation. They do not co-occur strictly with replication, their frequency varies with growth condition and chromosomal coordinate, and they show a preference for longitudinal motion. These findings support an emerging picture of the bacterial chromosome as off-equilibrium active matter and help developing a correct physical model of its in vivo dynamic structure.

Mapping the driving forces of chromosome structure and segregation in Escherichia coli.

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.

Quantitative single-cell characterization of bacterial interactions reveals type VI secretion is a double-edged sword.

Interbacterial interaction pathways play an important role in defining the structure and complexity of bacterial associations. A quantitative description of such pathways offers promise for understanding the forces that contribute to community composition. We developed time-lapse fluorescence microscopy methods for quantitation of interbacterial interactions and applied these to the characterization of type VI secretion (T6S) in Pseudomonas aeruginosa. Our analyses allowed a direct determination of the efficiency of recipient cell lysis catalyzed by this intercellular toxin delivery pathway and provided evidence that its arsenal extends beyond known effector proteins. Measurement of T6S apparatus localization revealed correlated activation among neighboring cells, which, taken together with genetic data, implicate the elaboration of a functional T6S apparatus with a marked increase in susceptibility to intoxication. This possibility was supported by the identification of T6S-inactivating mutations in a genome-wide screen for resistance to T6S-mediated intoxication and by time-lapse fluorescence microscopy analyses showing a decreased lysis rate of recipient cells lacking T6S function. Our discoveries highlight the utility of single-cell approaches for measuring interbacterial phenomena and provide a foundation for studying the contribution of a widespread bacterial interaction pathway to community structure.

Surface sensing and lateral subcellular localization of WspA, the receptor in a chemosensory-like system leading to c-di-GMP production.

Pseudomonas aeruginosa responds to growth on agar surfaces to produce cyclic-di-GMP, which stimulates biofilm formation. This is mediated by an alternative cellular function chemotaxis-like system called Wsp. The receptor protein WspA, is bioinformatically indistinguishable from methyl-accepting chemotaxis proteins. However, unlike standard chemoreceptors, WspA does not form stable clusters at cell poles. Rather, it forms dynamic clusters at both polar and lateral subcellular locations. To begin to study the mechanism of Wsp signal transduction in response to surfaces, we carried out a structure-function study of WspA and found that its C-terminus is important for its lateral subcellular localization and function. When this region was replaced with that of a chemoreceptor for amino acids, WspA became polarly localized. In addition, introduction of mutations in the C-terminal region of WspA that rendered this protein able to form more stable receptor-receptor interactions, also resulted in a WspA protein that was less capable of activating signal transduction. Receptor chimeras with a WspA C-terminus and N-terminal periplasmic domains from chemoreceptors that sense amino acids or malate responded to surfaces to produce c-di-GMP. Thus, the amino acid sequence of the WspA periplasmic region did not need to be conserved for the Wsp system to respond to surfaces.

Tuning the performance of an artificial protein motor.

The Tumbleweed (TW) is a concept for an artificial, tri-pedal, protein-based motor designed to move unidirectionally along a linear track by a diffusive tumbling motion. Artificial motors offer the unique opportunity to explore how motor performance depends on design details in a way that is open to experimental investigation. Prior studies have shown that TW's ability to complete many successive steps can be critically dependent on the motor's diffusional step time. Here, we present a simulation study targeted at determining how to minimize the diffusional step time of the TW motor as a function of two particular design choices: nonspecific motor-track interactions and molecular flexibility. We determine an optimal nonspecific interaction strength and establish a set of criteria for optimal molecular flexibility as a function of the nonspecific interaction. We discuss our results in the context of similarities to biological, linear stepping diffusive molecular motors with the aim of identifying general engineering principles for protein motors.

The Tumbleweed: towards a synthetic proteinmotor.

Biomolecular motors have inspired the design and construction of artificial nanoscale motors and machines based on nucleic acids, small molecules, and inorganic nanostructures. However, the high degree of sophistication and efficiency of biomolecular motors, as well as their specific biological function, derives from the complexity afforded by protein building blocks. Here, we discuss a novel bottom-up approach to understanding biological motors by considering the construction of synthetic protein motors. Specifically, we present a design for a synthetic protein motor that moves along a linear track, dubbed the "Tumbleweed." This concept uses three discrete ligand-dependent DNA-binding domains to perform cyclically ligand-gated, rectified diffusion along a synthesized DNA molecule. Here we describe how de novo peptide design and molecular biology could be used to produce the Tumbleweed, and we explore the fundamental motor operation of such a design using numerical simulations. The construction of this and more sophisticated protein motors is an exciting challenge that is likely to enhance our understanding of the structure-function relationship in biological motors.

Realization of a feedback controlled flashing ratchet.

A flashing ratchet transports diffusive particles using a time-dependent, asymmetric potential. The particle speed is predicted to increase when a feedback algorithm based on the particle position is used. We have experimentally realized such a feedback ratchet using an optical line trap, and observed that use of feedback increases velocity by up to an order of magnitude. We compare two different feedback algorithms for small particle numbers, and find good agreement with simulations. We also find that existing algorithms can be improved to be more tolerant to feedback delay times.