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Two powerful and complementary experimental approaches are commonly used to study the cell cycle and cell biology: One class of experiments characterizes the statistics (or demographics) of an unsynchronized exponentially-growing population, while the other captures cell cycle dynamics, either by time-lapse imaging of full cell cycles or in bulk experiments on synchronized populations. In this paper, we study the subtle relationship between observations in these two distinct experimental approaches. We begin with an existing model: a single-cell deterministic description of cell cycle dynamics where cell states (i.e. periods or phases) have precise lifetimes. We then generalize this description to a stochastic model in which the states have stochastic lifetimes, as described by arbitrary probability distribution functions. Our analyses of the demographics of an exponential culture reveal a simple and exact correspondence between the deterministic and stochastic models: The corresponding state lifetimes in the deterministic model are equal to the exponential mean of the lifetimes in the stochastic model. An important implication is therefore that the demographics of an exponential culture will be well-fit by a deterministic model even if the state timing is stochastic. Although we explore the implications of the models in the context of the Escherichia coli cell cycle, we expect both the models as well as the significance of the exponential-mean lifetimes to find many applications in the quantitative analysis of cell cycle dynamics in other biological systems.

When bacterial cells come in contact, antagonism mediated by the delivery of toxins frequently ensues. The potential for such encounters to have long-term beneficial consequences in recipient cells has not been investigated. Here, we examined the effects of intoxication by DddA, a cytosine deaminase delivered via the type VI secretion system (T6SS) of Burkholderia cenocepacia. Despite its killing potential, we observed that several bacterial species resist DddA and instead accumulate mutations. These mutations can lead to the acquisition of antibiotic resistance, indicating that even in the absence of killing, interbacterial antagonism can have profound consequences on target populations. Investigation of additional toxins from the deaminase superfamily revealed that mutagenic activity is a common feature of these proteins, including a representative we show targets single-stranded DNA and displays a markedly divergent structure. Our findings suggest that a surprising consequence of antagonistic interactions between bacteria could be the promotion of adaptation via the action of directly mutagenic toxins.

Entry into sporulation in Bacillus subtilis is governed by a phosphorelay in which phosphoryl groups from a histidine kinase are successively transferred via relay proteins to the response regulator Spo0A. Spo0A~P, in turn, sets in motion events that lead to asymmetric division and activation of the cell-specific transcription factor σF, a hallmark for entry into sporulation. Here, we have used a microfluidics-based platform to investigate the activation of Spo0A and σF in individual cells held under constant, sporulation-inducing conditions. The principal conclusions were that: (i) activation of σF occurs with an approximately constant probability after adaptation to conditions of nutrient limitation; (ii) activation of σF is tightly correlated with, and preceded by, Spo0A~P reaching a high threshold level; (iii) activation of Spo0A takes place abruptly just prior to asymmetric division; and (iv) the primary source of noise in the activation of Spo0A is the phosphorelay. We propose that cells exhibit a constant probability of attaining a high threshold level of Spo0A~P due to fluctuations in the flux of phosphoryl groups through the phosphorelay.

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.

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 micro-colonies 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 neighboring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of post-processing 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. This article is protected by copyright. All rights reserved.

ADP-ribosylation of proteins can profoundly impact their function and serves as an effective mechanism by which bacterial toxins impair eukaryotic cell processes. Here, we report the discovery that bacteria also employ ADP-ribosylating toxins against each other during interspecies competition. We demonstrate that one such toxin from Serratia proteamaculans interrupts the division of competing cells by modifying the essential bacterial tubulin-like protein, FtsZ, adjacent to its protomer interface, blocking its capacity to polymerize. The structure of the toxin in complex with its immunity determinant revealed two distinct modes of inhibition: active site occlusion and enzymatic removal of ADP-ribose modifications. We show that each is sufficient to support toxin immunity; however, the latter additionally provides unprecedented broad protection against non-cognate ADP-ribosylating effectors. Our findings reveal how an interbacterial arms race has produced a unique solution for safeguarding the integrity of bacterial cell division machinery against inactivating post-translational modifications.

The type VI secretion system (T6SS) inhibits the growth of neighboring bacterial cells through a contact-mediated mechanism. Here, we describe a detailed characterization of the protein localization dynamics in the Pseudomonas aeruginosa T6SS. It has been proposed that the type VI secretion process is driven by a conformational-change-induced contraction of the T6SS sheath. However, although the contraction of an optically resolvable TssBC sheath and the subsequent localization of ClpV are observed in Vibrio cholerae , coordinated assembly and disassembly of TssB and ClpV are observed without TssB contraction in P. aeruginosa . These dynamics are inconsistent with the proposed contraction sheath model. Motivated by the phenomenon of dynamic instability, we propose a new model in which ATP hydrolysis, rather than conformational change, generates the force for secretion. IMPORTANCE The type VI secretion system (T6SS) is widely conserved among Gram-negative bacteria and is a central determinant of bacterial fitness in polymicrobial communities. The secretion system targets bacteria and secretes effectors that inhibit the growth of neighboring cells, using a contact-mediated-delivery system. Despite significant homology to the previously characterized Vibrio cholerae T6SS, our analysis reveals that effector secretion is driven by a distinct force generation mechanism in Pseudomonas aeruginosa . The presence of two distinct force generation mechanisms in T6SS represents an example of the evolutionary diversification of force generation mechanisms.

DNA replication is essential to cellular proliferation. The cellular-scale organization of the replication machinery (replisome) and the replicating chromosome has remained controversial. Two competing models describe the replication process: In the track model, the replisomes translocate along the DNA like a train on a track. Alternately, in the factory model, the replisomes form a stationary complex through which the DNA is pulled. We summarize the evidence for each model and discuss a number of confounding aspects that complicate interpretation of the observations. We advocate a factory-like model for bacterial replication where the replisomes form a relatively stationary and weakly associated complex that can transiently separate.

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data.

Despite the innate complexity of the cell, emergent scale-invariant behavior is observed in many biological systems. We investigate one example of this phenomenon: the dynamics of large complexes in the bacterial cytoplasm. The observed dynamics of these complexes is scale invariant in three measures of dynamics: mean-squared displacement (MSD), velocity autocorrelation function, and the step-size distribution. To investigate the physical mechanism for this emergent scale invariance, we explore minimal models in which mobility is modeled as diffusion on a rough free-energy landscape in one dimension. We discover that all three scale-invariant characteristics emerge generically in the strong disorder limit. (Strong disorder is defined by the divergence of the ensemble-averaged hop time between lattice sites.) In particular, we demonstrate how the scale invariance of the relative step-size distribution can be understood from the perspective of extreme-value theory in statistics (EVT). We show that the Gumbel scale parameter is simply related to the MSD scaling parameter. The EVT mechanism of scale invariance is expected to be generic to strongly disordered systems and therefore a powerful tool for the analysis of other systems in biology and beyond.

The positioning of the DNA replication machinery (replisome) has been the subject of several studies. Two conflicting models for replisome localization have been proposed: In the Factory Model, sister replisomes remain spatially co-localized as the replicating DNA is translocated through a stationary replication factory. In the Track Model, sister replisomes translocate independently along a stationary DNA track and the replisomes are spatially separated for the majority of the cell cycle. Here, we used time-lapse imaging to observe and quantify the position of fluorescently labeled processivity-clamp (DnaN) complexes throughout the cell cycle in two highly-divergent bacterial model organisms: Bacillus subtilis and Escherichia coli. Because DnaN is a core component of the replication machinery, its localization patterns should be an appropriate proxy for replisome positioning in general. We present automated statistical analysis of DnaN positioning in large populations, which is essential due to the high degree of cell-to-cell variation. We find that both bacteria show remarkably similar DnaN positioning, where any potential separation of the two replication forks remains below the diffraction limit throughout the majority of the replication cycle. Additionally, the localization pattern of several other core replisome components is consistent with that of DnaN. These data altogether indicate that the two replication forks remain spatially co-localized and mostly function in close proximity throughout the replication cycle. The conservation of the observed localization patterns in these highly divergent species suggests that the subcellular positioning of the replisome is a functionally critical feature of DNA replication., Author Summary Cell proliferation depends on efficient replication of the genome. Bacteria typically have a single origin of replication on a circular chromosome. After replication initiation, two replisomes assemble at the origin and each copy one of the two arms of the chromosome until they reach the terminus. There have been conflicting reports about the subcellular positioning and putative co-localization of the two replication forks during this process. It has remained controversial whether the two replisomes remain relatively close to each other with the DNA being pulled through, or separate as they translocate along the DNA like a track. Existing studies have relied heavily on snapshot images and these experiments cannot unambiguously distinguish between these two models: i.e. two resolvable forks versus two pairs of co-localized forks. The ability of replication to re-initiate before cell division in bacterial cells further complicates the interpretation of these types of imaging studies. In this paper, we use a combination of snapshot imaging, time-lapse imaging, and quantitative analysis to measure the fraction of time forks are co-localized during each cell cycle. We find that the forks are co-localized for the majority (80%) of the replication cycle in two highly-divergent model organisms: B. subtilis and E. coli. Our observations are consistent with proximal localization of the two forks, but also some transient separations of sister forks during replication. The conserved behavior of sub-cellular positioning of the replisomes in these two highly divergent species implies a potential functional relevance of this feature.

The canonical model of DNA replication describes a highly-processive and largely continuous process by which the genome is duplicated. This continuous model is based upon in vitro reconstitution and in vivo ensemble experiments. Here, we characterize the replisome-complex stoichiometry and dynamics with single-molecule resolution in bacterial cells. Strikingly, the stoichiometries of the replicative helicase, DNA polymerase, and clamp loader complexes are consistent with the presence of only one active replisome in a significant fraction of cells (>40%). Furthermore, many of the observed complexes have short lifetimes (

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.

To characterize the consequences of eliminating essential functions needed for peptidoglycan synthesis, we generated deletion mutations of Acinetobacter baylyi by natural transformation and visualized the resulting microcolonies of dead cells. We found that loss of genes required for peptidoglycan precursor synthesis or polymerization led to the formation of polymorphic giant cells with diameters that could exceed ten times normal. Treatment with antibiotics targeting early or late steps of peptidoglycan synthesis also produced giant cells. The giant cells eventually lysed, although they were partially stabilized by osmotic protection. Genome-scale transposon mutant screening (Tn-seq) identified mutations that blocked or accelerated giant cell formation. Among the mutations that blocked the process were those inactivating a function predicted to cleave murein glycan chains (the MltD murein lytic transglycosylase), suggesting that giant cell formation requires MltD hydrolysis of existing peptidoglycan. Among the mutations that accelerated giant cell formation after ß-lactam treatment were those inactivating an enzyme that produces unusual 3->3 peptide cross-links in peptidoglycan (the LdtG L,D-transpeptidase). The mutations may weaken the sacculus and make it more vulnerable to further disruption. Although the study focused on A. baylyi, we found that a pathogenic relative (A. baumannii) also produced giant cells with genetic dependencies overlapping those of A. baylyi. Overall, the analysis defines a genetic pathway for giant cell formation conserved in Acinetobacter species in which independent initiating branches converge to create the unusual cells., Author summary Although essential genes control the most basic functions of bacterial life, they are difficult to study genetically because mutants lacking the functions die. We have developed a simple procedure for creating bacteria in which different essential genes have been completely deleted, making it possible to analyze the roles of the missing functions based on the features of the dead cells that result. When genes needed for the production of the cell wall were inactivated, the bacteria formed bizarre giant cells. It was possible to identify the functions responsible for forming the giant cells, and to formulate a model for how they form. Since cell wall synthesis is one of the most important antibiotic targets, understanding how bacteria respond to its disruption may ultimately help in developing procedures to overcome antibiotic resistant bacterial infections.

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.

Membranes allow the compartmentalization of biochemical processes and are therefore fundamental to life. The conservation of the cellular membrane, combined with its accessibility to secreted proteins, has made it a common target of factors mediating antagonistic interactions between diverse organisms. Here we report the discovery of a diverse superfamily of bacterial phospholipase enzymes. Within this superfamily, we defined enzymes with phospholipase A1 (PLA1) and A2 (PLA2) activity, which are common in host cell-targeting bacterial toxins and the venoms of certain insects and reptiles1,2. However, we find that the fundamental role of the superfamily is to mediate antagonistic bacterial interactions as effectors of the type VI secretion system (T6SS) translocation apparatus; accordingly, we name these proteins type VI lipase effectors (Tle). Our analyses indicate that PldA of Pseudomonas aeruginosa, a eukaryotic-like phospholipase D (PLD)3, is a member of the Tle superfamily and the founding substrate of the haemolysin co-regulated protein secretion island II T6SS (H2-T6SS). While prior studies have specifically implicated PldA and the H2-T6SS in pathogenesis3–5, we uncovered a specific role for the effector and its secretory machinery in intra- and inter-species bacterial interactions. Furthermore we find that this effector achieves its antibacterial activity by degrading phosphatidylethanolamine (PE), the major component of bacterial membranes. The surprising finding that virulence-associated phospholipases can serve as specific antibacterial effectors suggests that interbacterial interactions are a relevant factor driving the ongoing evolution of pathogenesis.

The cellular cytoplasm is a complex, heterogeneous environment (both spatially and temporally) that exhibits viscoelastic behavior. To further develop our quantitative insight into cellular transport, we analyze data sets of mRNA molecules fluorescently labeled with MS2-GFP tracked in real time in live Escherichia coli and Saccharomyces cerevisiae cells. As shown previously, these RNA-protein particles exhibit subdiffusive behavior that is viscoelastic in its origin. Examining the ensemble of particle displacements reveals a Laplace distribution at all observed timescales rather than the Gaussian distribution predicted by the central limit theorem. This ensemble non-Gaussian behavior is caused by a combination of an exponential distribution in the time-averaged diffusivities and non-Gaussian behavior of individual trajectories. We show that the non-Gaussian behavior is a consequence of significant heterogeneity between trajectories and dynamic heterogeneity along single trajectories. Informed by theory and simulation, our work provides an in-depth analysis of the complex diffusive behavior of RNA-protein particles in live cells.

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.

Change-point analysis is a flexible and computationally tractable tool for the analysis of times series data from systems that transition between discrete states and whose observables are corrupted by noise. The change-point algorithm is used to identify the time indices (change points) at which the system transitions between these discrete states. We present a unified information-based approach to testing for the existence of change points. This new approach reconciles two previously disparate approaches to Change-Point Analysis (frequentist and information-based) for testing transitions between states. The resulting method is statistically principled, parameter and prior free and widely applicable to a wide range of change-point problems., Comment: 10 pages + supplement. 5 Figures

The perception and response to cellular death is an important aspect of multicellular eukaryotic life. For example, damage-associated molecular patterns activate an inflammatory cascade that leads to removal of cellular debris and promotion of healing. We demonstrate that lysis of Pseudomonas aeruginosa cells triggers a program in the remaining population that confers fitness in interspecies co-culture. We find that this program, termed P. aeruginosa response to antagonism (PARA), involves rapid deployment of antibacterial factors and is mediated by the Gac/Rsm global regulatory pathway. Type VI secretion, and, unexpectedly, conjugative type IV secretion within competing bacteria, induce P. aeruginosa lysis and activate PARA, thus providing a mechanism for the enhanced capacity of P. aeruginosa to target bacteria that elaborate these factors. Our finding that bacteria sense damaged kin and respond via a widely distributed pathway to mount a complex response raises the possibility that danger sensing is an evolutionarily conserved process. DOI: http://dx.doi.org/10.7554/eLife.05701.001, eLife digest Bacteria live in diverse and changing environments where resources such as nutrients and space are often limited. They have thus evolved many survival strategies, including competitive and cooperative behaviors. In the first case, bacteria antagonize or prevent the growth of other microorganisms competing with them for resources, such as by generating antibiotics that specifically target rivals. During cooperation, bacteria may coordinate the production of compounds that have a shared benefit for members of their community. In multicellular organisms, some cell types sense harmful microorganisms by the injury they cause in neighboring cells. This triggers a process that can lead to the production of molecules that kill the invaders and factors that promote the repair of cellular damage. An equivalent process has so far not been described for single-celled organisms such as bacteria. However, bacteria often live in structured groups containing many different species. In this type of growth environment, the ability of bacteria to sense when others of their species are attacked and to respond by taking measures to defend themselves could improve their chances of survival. Now, LeRoux et al. reveal that the bacterium Pseudomonas aeruginosa is able to detect ‘danger signals’ released when neighboring P. aeruginosa cells are killed by other bacteria. These signals trigger a response in surviving cells by turning on a pathway that controls a number of antibacterial factors. These include the production of the so-called ‘type VI secretion system’, a molecular machine that delivers a potent cocktail of antibacterial toxins directly into nearby bacteria. This process, which LeRoux et al. have named ‘P. aeruginosa response to antagonism’, or PARA for short, enables P. aeruginosa to thrive when grown with competing bacterial species. P. aeruginosa is notorious for infecting the lungs of people with the genetic disease cystic fibrosis, as well as chronic wounds often found in people with diabetes. In both cases, when P. aeruginosa is present, the numbers of other, often less harmful organisms, tend to decrease. PARA may be one reason for the success of P. aeruginosa in these multi-species infections. DOI: http://dx.doi.org/10.7554/eLife.05701.002

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 t0.32. 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.

Because RNA lacks strong intrinsic fluorescence, it has proven challenging to track RNA molecules in real time. To address this problem and to allow the purification of fluorescently tagged RNA complexes, we have selected a high affinity RNA aptamer called RNA Mango. This aptamer binds a series of thiazole orange (fluorophore) derivatives with nanomolar affinity, while increasing fluorophore fluorescence by up to 1,100-fold. Visualization of RNA Mango by single-molecule fluorescence microscopy, together with injection and imaging of RNA Mango/fluorophore complex in C. elegans gonads demonstrates the potential for live-cell RNA imaging with this system. By inserting RNA Mango into a stem loop of the bacterial 6S RNA and biotinylating the fluorophore, we demonstrate that the aptamer can be used to simultaneously fluorescently label and purify biologically important RNAs. The high affinity and fluorescent properties of RNA Mango are therefore expected to simplify the study of RNA complexes.

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.

In recent years, evidence has emerged that the bacterial chromosome possesses a remarkable level of spatial and temporal organization, and its structural changes are believed to have an important role in key cellular functions, such as regulating transcription.Particle tracking of chromosomal loci is possible by constructing strains in which GFP adheres to a particular genomic site. This has been used by several labs over the last few years both as a technique to map out the “home position” of each genomic site within the cell body, and to study the fluctuation properties. It has become a key technique in the development of a correct physical model to capture the in vivo structure and functional organization.Our analysis of chromosomal dynamics investigated the short time (0.1s-10s) regime, published in [1], showing a decrease in motility in loci near the terminus of replication. This chromosomal trend is maintained across different growth conditions and appears to be related with the positioning of Ter in mid-cell position during chromosomal replication.In unpublished work, we have compared the observed foci behavior with a physical model of subdiffusive dynamics, and we have found a small subset of ubiquitous “rapid movements” that exhibit near ballistic dynamics. This suggests the presence of an active driving machinery, or stress relaxation mechanisms that are non-trivially coupled with chromosomal partitioning; in either case, non-thermal fluctuations are present in the chromosome.Finally, we have studied the effect on chromosomal dynamics induced by that chemical perturbations and in knockout mutants lacking certain nucleoid associated proteins.[1] Javer, et al. “Short-time movement of E. coli chromosomal loci depends on coordinate and subcellular localization.” Nature communications 4 (2013).

Ever since Hershey and Chase used phages to establish DNA as the carrier of genetic information in 1952, the precise mechanisms of phage DNA translocation have been a mystery. While bulk measurements have set a time scale for in vivo DNA translocation during bacteriophage infection, measurements of DNA ejection by single bacteriophages have only been made in vitro. Here, we present direct visualization of single bacteriophages infecting individual Escherichia coli cells. For bacteriophage lambda, we establish a mean ejection time of roughly 5 minutes with significant cell-to-cell variability, including pausing events. In contrast, corresponding in vitro single-molecule ejections take only 10 seconds to reach completion and do not exhibit significant variability. Our data reveal that the velocity of ejection for two different genome lengths collapses onto a single curve. This suggests that in vivo ejections are controlled by the amount of DNA ejected, in contrast with in vitro DNA ejections, which are governed by the amount of DNA left inside the capsid. This analysis provides evidence against a purely intrastrand repulsion based mechanism, and suggests that cell-internal processes dominate. This provides a picture of the early stages of phage infection and sheds light on the problem of polymer translocation., Comment: Current Biology (2012); published version available at http://www.cell.com/current-biology/abstract/S0960-9822(12)00576-3

Studies of membrane proteins have revealed a direct link between the lipid environment and the structure and function of some of these proteins. Although some of these effects involve specific chemical interactions between lipids and protein residues, many can be understood in terms of protein-induced perturbations to the membrane shape. The free-energy cost of such perturbations can be estimated quantitatively, and measurements of channel gating in model systems of membrane proteins with their lipid partners are now confirming predictions of simple models.

DNA bending on length scales shorter than a persistence length plays an integral role in the translation of genetic information from DNA to cellular function. Quantitative experimental studies of these biological systems have led to a renewed interest in the polymer mechanics relevant for describing the conformational free energy of DNA bending induced by protein-DNA complexes. Recent experimental results from DNA cyclization studies have cast doubt on the applicability of the canonical semiflexible polymer theory, the wormlike chain (WLC) model, to DNA bending on biologically relevant length scales. This paper develops a theory of the chain statistics of a class of generalized semiflexible polymer models. Our focus is on the theoretical development of these models and the calculation of experimental observables. To illustrate our methods, we focus on a specific, illustrative model of DNA bending. We show that the WLC model generically describes the long-length-scale chain statistics of semiflexible polymers, as predicted by renormalization group arguments. In particular, we show that either the WLC or our present model adequately describes force-extension, solution scattering, and long-contour-length cyclization experiments, regardless of the details of DNA bend elasticity. In contrast, experiments sensitive to short-length-scale chain behavior can in principle reveal dramatic departures from the linear elastic behavior assumed in the WLC model. We demonstrate this explicitly by showing that our toy model can reproduce the anomalously large short-contour-length cyclization J factors recently measured by Cloutier and Widom. Finally, we discuss the applicability of these models to DNA chain statistics in the context of future experiments.

In this paper, we examine the mechanical role of the lipid bilayer in ion channel conformation and function with specific reference to the case of the mechanosensitive channel of large conductance (MscL). In a recent paper (Wiggins and Phillips, 2004), we argued that mechanotransduction very naturally arises from lipid-protein interactions by invoking a simple analytic model of the MscL channel and the surrounding lipid bilayer. In this paper, we focus on improving and expanding this analytic framework for studying lipid-protein interactions with special attention to MscL. Our goal is to generate simple scaling relations which can be used to provide qualitative understanding of the role of membrane mechanics in protein function and to quantitatively interpret experimental results. For the MscL channel, we find that the free energies induced by lipid-protein interaction are of the same order as the free energy differences between conductance states measured by Sukharev et al. (1999). We therefore conclude that the mechanics of the bilayer plays an essential role in determining the conformation and function of the channel. Finally, we compare the predictions of our model to experimental results from the recent investigations of the MscL channel by Perozo et al. (2002), Powl et al. (2003), Yoshimura et al. (2004), and others and suggest a suite of new experiments.

The importance of nonlinearities in material constitutive relations has long been appreciated in the continuum mechanics of macroscopic rods. Although the moment (torque) response to bending is almost universally linear for small deflection angles, many rod systems exhibit a high-curvature softening. The signature behavior of these rod systems is a kinking transition in which the bending is localized. Recent DNA cyclization experiments by Cloutier and Widom have offered evidence that the linear-elastic bending theory fails to describe the high-curvature mechanics of DNA. Motivated by this recent experimental work, we develop a simple and exact theory of the statistical mechanics of linear-elastic polymer chains that can undergo a kinking transition. We characterize the kinking behavior with a single parameter and show that the resulting theory reproduces both the low-curvature linear-elastic behavior which is already well described by the Wormlike Chain model, as well as the high-curvature softening observed in recent cyclization experiments., Comment: Revised for PRE. 40 pages, 12 figures

Independent measurements of the elastic modulus (Young's modulus) of tissue are a necessary step in turning elasticity imaging into a clinical tool. A system capable of measuring the elastic modulus of small tissue samples was developed. The system tolerates the constraints of biological tissue, such as limited sample size (≤1.5 cm3) and imperfections in sample geometry. A known deformation is applied to the tissue sample while simultaneously measuring the resulting force. These measurements are then converted to an elastic modulus, where the conversion uses prior calibration of the system with plastisol samples of known Young's modulus. Accurate measurements have been obtained from 10 to 80 kPa, covering a wide range of tissue modulus values. In addition, the performance of the system was further investigated using finite element analysis. Finally, preliminary elasticity measurements on canine kidney samples are presented and discussed.