Abstract
Single-molecule fluorescence provides high resolution spatial distributions of ribosomes and RNA polymerase (RNAP) in live, rapidly growing Escherichia coli. Ribosomes are more strongly segregated from the nucleoids (chromosomal DNA) than previous widefield fluorescence studies suggested. While most transcription may be co-translational, the evidence indicates that most translation occurs on free mRNA copies that have diffused from the nucleoids to a ribosome-rich region. Analysis of time-resolved images of the nucleoid spatial distribution after treatment with the transcription-halting drug rifampicin and the translation-halting drug chloramphenicol shows that both drugs cause nucleoid contraction on the 0–3 min timescale. This is consistent with the transertion hypothesis. We suggest that the longer-term (20–30 min) nucleoid expansion after Rif treatment arises from conversion of 70S-polysomes to 30S and 50S subunits, which readily penetrate the nucleoids. Monte Carlo simulations of a polymer bead model built to mimic the chromosomal DNA and ribosomes (either 70S-polysomes or 30S and 50S subunits) explain spatial segregation or mixing of ribosomes and nucleoids in terms of excluded volume and entropic effects alone. A comprehensive model of the transcription-translation-transertion system incorporates this new information about the spatial organization of the E. coli cytoplasm. We propose that transertion, which radially expands the nucleoids, is essential for recycling of 30S and 50S subunits from ribosome-rich regions back into the nucleoids. There they initiate co-transcriptional translation, which is an important mechanism for maintaining RNAP forward progress and protecting the nascent mRNA chain. Segregation of 70S-polysomes from the nucleoid may facilitate rapid growth by shortening the search time for ribosomes to find free mRNA concentrated outside the nucleoid and the search time for RNAP concentrated within the nucleoid to find transcription initiation sites.
Introduction
Super-resolution fluorescence methods (; ; Rust et al., 2006) enable detailed exploration of the ways in which the central dogma of molecular biology plays out in Escherichia coli. “Photoactivation-localization microscopy” (PALM) can locate and track 1000s of copies of single, specific proteins in live cells with ∼30 nm spatial resolution and low-ms time resolution. This has enabled detailed, quantitative studies of how ribosomes (), chromosomal DNA (Wang et al., 2011), and RNA polymerase (RNAP; , ; ) are distributed in space and move in time within the cytoplasm of single cells. In addition, time-resolved widefield fluorescence imaging after drug treatment has provided new insight into the ways in which transcription and translation determine the internal organization of cytoplasm (). Transcription, translation, and the spatial organization of E. coli cytoplasm act as a coupled biochemical–biophysical system. Here, we describe the delicate balance of forces that enables the system to drive rapid cell growth.
In E. coli, the chromosomal DNA occupies the region of space called the nucleoids (Kellenberger, 1991). During rapid growth, ribosomes are concentrated outside the nucleoids in ribosome-rich regions comprising the two polar end-caps, the space between nucleoid lobes, and the thin region proximal to the cytoplasmic membrane (Figure 1; ). The spatial extent of the nucleoids evidently arises from a balance of compacting and expanding forces (Woldringh et al., 1995; Zimmerman, 2006). Likely compacting forces include depletion-attraction of DNA arising from macromolecular crowding by myriad small proteins (Zimmerman and Murphy, 1996); conformational entropy of the confined DNA polymer, which causes the polymer to avoid walls (Mondal et al., 2011; ); inter-strand coupling by DNA binding proteins such as H-NS (; Wang et al., 2011); bending of DNA by IHF (); and net supercoiling of the DNA by Gyrase and Topoisomerase I (Woldringh et al., 1995). The hypothesized primary expanding force is “transertion,” which is the simultaneous co-transcriptional translation and insertion of membrane proteins via the translocon machinery (Woldringh, 2002). Transertion implies the existence of DNA-RNAP-mRNA-ribosome-polypeptide-membrane “transertion chains” directly linking DNA to the membrane (Figure 1). A sufficient number of these chains would radially expand the overall nucleoid. The main evidence for transertion had been the dramatic contraction of the nucleoids on treatment with translation-halting drugs such as chloramphenicol (van Helvoort et al., 1996; Zimmerman, 2002). Treatment with transcription-halting drugs such as rifampicin should have the same effect, but this was not observed on the 30-min timescale studied (; ). Our recent time-dependent imaging study discovered nucleoid contraction on a 3-min timescale after rifampicin treatment, placing the transertion hypothesis on solid footing ().
FIGURE 1
In rapidly growing E. coli, only 10–15% of ribosomal subunits lie within the nucleoids (
A number of earlier studies used physical models to explain the formation of compact nucleoids that occupy only a fraction of the entire bacterial cytoplasm. A statistical mechanical model used the osmotic effects of myriad small proteins to explain the apparent phase separation (Odijk, 1998). A recent experimental study of free bacterial nucleoids confined in a microfluidic channel showed that crowding by added polyethylene glycine chains (PEG) led to reversible, first-order “coil-to-globule” collapse of the nucleoids (Pelletier et al., 2012). This study augmented the earlier statistical model to include the entropic spring nature of the nucleoids. A very recent coarse-grained simulation showed that small, spherical crowding agents can induce compaction of a DNA polymer, modeled as a freely jointed chain (Shendruk et al., 2015).
We have found that a simple physical model using Monte Carlo simulations of DNA and ribosome spatial distributions in a confining cytoplasmic space enhances our understanding of the observed ribosome-nucleoid segregation (Mondal et al., 2011). In the model, entropic and excluded volume effects cause strong segregation of the unperturbed nucleoid from 70S-polysomes. The biochemical state of ribosomes (70S-polysomes vs. free 30S and 50S subunits) plays an essential role in ribosome-nucleoid segregation. When the model 70S-polysomes are converted to 30S and 50S subunits, the components mix quite thoroughly with the DNA and the nucleoid expands (
Based on these new experimental and computational results, we are developing a comprehensive model of the spatial organization within the E. coli cytoplasm and how it may work to optimize cell growth. Our present view encompasses a variety of inter-related phenomena: (1) In rapidly growing cells, most translation occurs in the ribosome-rich regions, not within the nucleoids. (2) Yet there is direct evidence of co-transcriptional translation (Miller et al., 1970), and this is important for protecting nascent mRNA from degradation and for efficient transcription. Evidently most or all transcription is co-translational, but only ∼10–15% of translation is co-transcriptional. (3) Therefore 30S and 50S subunits must be able to penetrate the nucleoid where they initiate co-transcriptional translation (Sanamrad et al., 2014). This picture implies a circulation of 30S and 50S subunits between the nucleoids and the ribosome-rich regions. (4) Transertion expands the nucleoids beyond their relaxed, highly compacted state (Woldringh, 2002). The evidence suggests that transertion plays an essential role, enabling 30S and 50S subunits to move into the nucleoids where they initiate co-transcriptional translation and form nascent 70S-polysomes.
In this view, the transcription and translation machinery and the spatial organization of the cytoplasm act as a coupled biochemical–biophysical system. Effective compartmentalization of the cytoplasm into ribosome-rich regions and DNA- and RNAP-rich nucleoids may enhance the efficiency of protein synthesis and the utilization of RNAP. Segregation of 70S-polysomes from the nucleoid may facilitate rapid growth by minimizing the search time for ribosomes to find the free mRNA concentrated outside the nucleoid and for RNAP concentrated within the nucleoid to find transcription initiation sites. This review describes the evidence behind the comprehensive picture, briefly compares E. coli with Caulobacter crescentus, and contrasts our “translation-centric” view of nucleoid morphology with a “transcription-centric” view (
Super-Resolution Imaging of Single Protein Copies in Live Bacterial Cells
Overview
Super-resolution fluorescence microscopy of specific proteins in live cells (Figure 2) was enabled by three key technical advances. First, genetic manipulations enable replacement of the gene for the target protein by a gene that appends a fluorescent protein to the target. This “GFP revolution” enables imaging of a specific target protein in a live cell (Zhang et al., 2002). But caution is needed. The fluorescent protein tags may affect the function, aggregation state, spatial distribution, or movement of the target protein (Landgraf et al., 2012).
FIGURE 2

Schematic of the super-resolution imaging method. (A) Each fluorescent molecule makes a diffraction-limited, essentially Gaussian image on the camera. A dense set of normal labels (blue images) makes overlapping images. In each imaging cycle, a sparse set of labels is photoactivated (red image) and localized from the well-isolated, single-molecule images. (B) An image of the spatial distribution is built up one molecule at a time over 100s or 1000s of optical cycles (upper “half-cells”). Successive images of the same molecule form a diffusive trajectory (lower “half-cells”).
Second, on a dark background a single fluorescent molecule can produce a punctal, high signal-to-noise image on a sensitive EMCCD camera (Vrljic et al., 2007). However, the full width at half maximum height (FWHM) of this image is broadened to ∼λ/2 = 260 nm for detection of green light with wavelength λ = 520 nm. This defines the diffraction limit of light for an optical microscope. Nevertheless, a well-isolated, slowly moving single fluorophore can be located and tracked far more accurately than the diffraction-limited width of its image. In a 1 μm diameter × 3 μm long E. coli cell, the localization accuracy for fluorescent proteins is photon- and background-limited to ∼30 nm in each of the two projected dimensions (
Third, the super-resolution fluorescence methods use “photoswitchable” fluorescent proteins as the labels to overcome the problem of spatial overlap of the myriad images of high copy number fluorescent proteins in small cells (Figure 2). For example, PALM and its variations enable sub-diffraction-limit imaging of the ∼50,000 labeled 30S-mEos2 ribosomal subunits, essentially by imaging them one or a few copies at a time (
The diffusive behavior of each individual copy then provides clues to its biochemical state (Lippincott-Schwartz and Patterson, 2009). For ribosomes, 70S-polysomes diffuse somewhat more slowly than 30S subunits searching for a translation initiation site (
Cell Growth and Preparation
Our preferred E. coli strain VH1000 is a modification of MG1655 with the PyrE defect repaired. VH1000 grown in EZRDM (“EZ rich, defined medium”; Neidhardt et al., 1974), MBM (MOPS-buffered minimal medium) using glucose as carbon source, or MBM with glycerol, provides access to a wide range of doubling time (30, 60, and 120 min, respectively, at 37°C). Most of the experiments described here were carried out in EZRDM at 30°C.
We maintain cells at well-defined, constant levels of nutrition and aeration throughout the imaging experiments (
Labeling Strategies
The use of λ-Red mediated recombination (
To image the overall spatial distribution of DNA in growing cells, we strongly prefer the non-perturbative stain SYTOX Orange over the more standard DAPI imaging (
Single-Molecule Localization and Tracking Methodology
The mEos2 constructs yield trajectories of mean length 10 frames and enable control of the time between frames. For each 1000 trajectories, we obtain ∼150 trajectories of length >18 frames. We spatially filter the images and fit single-molecule locations using a centroid algorithm (Wang et al., 2010;
A sequence of locations for a particular particle forms a diffusive trajectory. We analyze single-molecule diffusion data in a variety of ways. Plots of mean-square displacement vs. lag time τ, MSD(τ), are obtained as a running average over each trajectory and over all molecules. To test for sub-diffusion effects due to tethering or caging, MSD(τ) is compared with Monte Carlo random walk (free diffusion) model calculations within an appropriate confinement volume. To test for heterogeneity of diffusion, we compute histograms of single-molecule diffusion coefficients, estimated as Di = msdi(τ)/4τ, where msdi(τ) is the single-molecule mean-square displacement averaged over one trajectory. The aspect ratio of trajectories can also help distinguish sub-diffusion from free diffusion of single-molecules (
Ribosome-Nucleoid Segregation in Rapid, Exponential Growth
Background
Miller et al. (1970), in their EM study of the contents of the E. coli cytoplasm observed long DNA strands to which chains of ribosomes (“70S-polysomes”) were attached, direct evidence of translation coupled to transcription (“co-transcriptional translation”). That study inferred that all bacterial protein synthesis was co-transcriptional. The total amount of mRNA per cell and the ribosome copy number confirm the importance of polysomes and suggest their typical length to be about ten 70S per mRNA. Co-transcriptional translation evidently assists optimal cell growth. It helps protect nascent mRNA against early termination by Rho and against premature degradation by ribonucleases (Proshkin et al., 2010; McGary and Nudler, 2013). In addition, specific proteins bind simultaneously to both RNAP and the lead ribosome in a polysome chain (
However, evidence from EM studies of sections of fixed E. coli cells (Kellenberger, 1991) and from widefield immuno-staining of whole, fixed cells (
Our own widefield images of live E. coli with DNA stained with DRAQ5 and ribsosomes labeled with S2-YFP show clear anti-correlation in the axial spatial distributions of the two species (Figure 3). The “peak-to-valley” ratio of the ribosomes is about 1.5:1. Intriguingly, in the slow-growing species C. crescentus, ribosomes and DNA appear to be much more thoroughly mixed (Llopis et al., 2010).
FIGURE 3

(A) Widefield images of ribosomes (S2-YFP labeling) and DNA (DRAQ5 staining) in single E. coli cells. (B) Axial linescans of ribosome and DNA intensity vs. the long-axis coordinate x. Anti-correlation is evident. Adapted from
Superresolution Imaging of RNAP and Ribosomes
In
FIGURE 4

(A–C) Super-resolution imaging of the spatial distributions of RNA polymerase (β′-YFP labeling) in live E. coli. (C) Shows a histogram of locations projected onto the long axis of the cell in (B). (D–G) Super-resolution imaging of the spatial distributions of ribosomes (30S-YFP labeling) in live E. coli. (E) Shows two single copies imaged in one camera frame. (G) Shows an axial histogram of locations for the cell shown in (F). The gray regions in (C,G) are simulated histograms for a uniformly filled spherocylinder matching the length and radius of the single cell. Adapted from
In our study of RNAP motion, we labeled RNAP as β′-mEos2 expressed from the chromosome (
FIGURE 5

(A) Single-RNAP diffusive trajectories in live E. coli growing in EZRDM at 37°C. Labeling was β′-mEos2. Note two types of trajectory. (B) Distribution of estimated diffusion coefficients Di from single-RNAP trajectories. Fast and slow sub-populations are evident. Red and green curves are model distributions for the two components. Adapted from
In the ribosome imaging studies, we found that some 85–90% of the 30S-YFP copies lie in the “ribosome-rich regions” (
FIGURE 6

Inset: Single-ribosome diffusive trajectories from a live E. coli cell growing in EZRDM at 30°C. Labeling is S2-YFP. Main figure: Distribution of estimated single-ribosome diffusion coefficients Di. S2-mEos2 labeling. Two sub-populations are evident. Model sub-distributions are shown as green and orange dashed lines. Magenta line is their sum.
After complete synthesis of a protein in a ribosome-rich region, the newly free 30S and 50S subunits may engage in repeated rounds of translation in the ribosome-rich region, or “escape” back to the nucleoid region where they can re-initiate co-transcriptional translation (Figure 7). Accordingly, the Elf lab recently showed that the more rapidly diffusing 30S and 50S subunits penetrate the nucleoids while the slower 70S-polysomes are largely excluded (Sanamrad et al., 2014). This picture implies a circulation of ribosomal subunits from the nucleoids (where co-transcriptional translation occurs) to the ribosome-rich regions (where most protein synthesis occurs) and back again.
FIGURE 7

Schematic showing the suggested circulation of ribosomal subunits into and out of the nucleoids and the ribosome-rich regions.
In fast growth conditions, concentration of 70S-polysomes in ribosome-rich regions may enhance the rate of protein synthesis by shortening the search time for translation initiation sites by newly freed 30S and 50S subunits that have just completed synthesis of a protein. Such spatial separation of transcription from most translation in E. coli is somewhat reminiscent of eukaryotic cells. However, it occurs without compartmentalization of DNA within a nuclear membrane. The Monte Carlo simulations described below suggest that the underlying segregation mechanism may be primarily physical in nature.
What Driving Forces Induce Nucleoid-Ribosome Mixing or Segregation?
In spite of the 1.5 mm contour length of an E. coli chromosome, the nucleoids do not fill the entire volume of the 3–4 μm long, 1 μm diameter cytoplasm (Pettijohn, 1982; Robinow and Kellenberger, 1994). The irregular shape of the E. coli nucleoids may be governed by the ring topology of DNA and spatial confinement effects on the ring polymer (
Long-Term Effects of Chloramphenicol and Rifampicin on Nucleoid-Ribosome Morphology
It has long been known that transcription- and translation-halting drugs strongly affect nucleoid morphology. Typical imaging experiments have compared nucleoid morphology before and 20–30 min after drug treatment, usually using DAPI as the DNA stain. We used the non-perturbative DNA stain SYTOX Orange (
FIGURE 8

(A) SYTOX orange-stained image of chromosomal DNA in a live E. coli cell growing in EZRDM at 30°C. The nucleoid spatial extent is characterized by length LDNA and width WDNA measured as the full width at half-maximum height (FWHM) of intensity distributions projected onto the x and y axes. (B) Time-lapse sequences of images of nucleoids stained by SYTOX Orange. Times in minutes, scale bars are 1 mm. Untreated cells, Rif-treated cells, and Cam-treated cells as indicated. (C) Quantitative nucleoid width WDNA vs. time. Gray: mean behavior of a set of untreated cells. Blue: behavior of Rif-treated cells. Red: behavior of Cam-treated cells. For blue and red, heavy lines are averages of traces from many cells; shaded regions show the envelope of single-cell results that were averaged. Dashed line shows time of initiation of flow of drug. (D) Same as (C), but with relative nucleoid length plotted as LDNA/Lcell. Adapted from
On the 10–20 min timescale, the nucleoids of Cam-treated cells have become much more compact axially than normally growing cells, while the nucleoids of Rif-treated cells have expanded in both dimensions (Figures 8B,C). Similar long-term drug effects were observed in earlier work (
Nucleoid-Ribosome Mixing Hypothesis
These long-term drug effects have motivated a new nucleoid-ribosome mixing hypothesis (Figure 9;
FIGURE 9

Schematic of ribosome-nucleoid mixing hypothesis. 70S-polysomes and DNA strongly avoid each other, while free 30S and 50S subunits readily penetrate into the nucleoids. Adapted from
In this view, the drug studies reveal three “states” of the nucleoid-ribosome system. For normally growing, untreated cells, transertion expands the nucleoids, imposing a state of intermediate DNA density that prevents 70S polysomes and the chromosomal DNA from mixing while permitting 30S and 50S subunits to penetrate the nucleoids. Transertion may thus be essential for the initiation and maintenance of co-transcriptional translation of nascent mRNA in the dense regions of the nucleoids. Cam freezes ribosomal subunits as 70S-polysomes. Completion of transcription events will break the transertion chains and the 70S-polysomes will then be unable to make new chains. Over 20 min, the chromosomal DNA relaxes to a fully condensed state that excludes both 70S-polysomes and 30S and 50S subunits. The fraction of free 30S and 50S subunits becomes even smaller than in normal growth, enabling very strong compaction of the nucleoids. We suggest that this represents the relaxed volume of the nucleoids in the absence of the expanding force of transertion and in the near absence of free ribosomal subunits. Rif treatment also breaks the transertion links on the same timescale as Cam, the time over which transcription events are completed. Again, new transertion chains are prevented from forming. This leads to similar short-term contraction (see below). DNA mixing with 30S and 50S ribosomal subunits eventually occurs on the longer, 10–20 min timescale of mRNA degradation. This leads to the third, fully expanded state of the nucleoids, in which few 70S-polysomes exist and DNA and the 30S and 50S ribosomal subunits mix extensively. However, the nucleoids continue to avoid the cylindrical walls and especially the endcaps.
Simple Physical Model of Ribosomes and Nucleoids
In Mondal et al. (2011), we developed a simple physical model of plectonemic DNA and 70S-polysomes confined in a spherocylinder (as pictured in Figure 10A). DNA was modeled as a hyperbranched polymer (hard spheres and connecting rods). Based on estimates at the time (
FIGURE 10

(A) Hyper-branched polymer bead model of plectonemic DNA and 70S-polysomes. The red DNA beads exclude each other; the gray beads are invisible to the DNA beads but act as volume appropriately excluded to the polysomes. Polysomes are represented as freely jointed chains of spheres of appropriate size. (B) In Monte Carlo simulations, 70S-polysomes and DNA strongly avoid each other. (C) When the 70S-polysomes are dissociated into 50S and 30S monomers, the simulations show strong mixing and nucleoid expansion. Adapted from
Translational entropy is the entropy of movement in space. It increases with the number of free particles and with the volume available to the particles. DNA conformational entropy is determined by the number of conformational states available to the DNA polymer. In the model, these entropic plus excluded volume effects lead to strong segregation of DNA from 70S-polysomes (Figure 10B). The model DNA polymer, comprising beads connected by rods, avoids the walls and does not fill the cytoplasm. This is because placing a bead near a wall would eliminate many potential conformations of the polymer and hence decrease conformational entropy.
To help understand why Rif-induced dissociation of 70S-polysomes into 30S and 50S subunits enables mixing of free subunits with the DNA and nucleoid expansion, we have recently performed a new set of simulations based on the same simplified model of DNA (Figure 10C;
The model suggests that the primary driving force for mixing of chromosomal DNA with ribosomal subunits after Rif treatment is increased translational entropy. Each 70S-polysome 13-mer has become 26 independent subunits, each “demanding” its own translational entropy. We suggest that the nucleoid expands to provide the 30S and 50S subunits with access to more volume in which to move.
In real cells, the nucleoids adopt their most compact form after Cam treatment, which preserves most ribosomal subunits as 70S-polysomes. Importantly, in this highly compacted form the nucleoids exclude not only 70S-polysomes, but also free 30S subunits (Sanamrad et al., 2014), LacI (Kuhlman and Cox, 2012), and the Kaede tetramer (
Co-transcriptional translation in turn is biologically important for preventing premature degradation of mRNA by endonucleases, termination of transcription by Rho, and excessive backtracking by RNAP. Thus transertion, whose very existence has long been debated, may be essential to optimal cell growth.
In our view, the overall physiological state of the cell (slow growth, fast growth, stationary phase, stress response, etc.) determines the number of ribosomal subunits and their partitioning between 70S-polysomes and 30S and 50S subunits. The Monte Carlo modeling then suggests that at least in rapid growth, the corresponding coarse nucleoid morphology is dictated by the tendency of the combined nucleoid-ribosome system to maximize total conformational and translational entropy. The modeling further suggests that in the presence of free 30S and 50S subunits, the tendency to maximize translational entropy of ribosomal subunits provides a second expanding force on the nucleoids, in addition to transertion. This tendency is most evident after treatment with the transcription-halting drug Rif. It is less evident, but may still be a significant effect, in normal growth when 30S and 50S subunits are minority ribosomal species. Our model of the factors controlling the overall DNA spatial distribution might be called “translation-centric,” because it emphasizes the importance of the DNA-ribosome system.
It is difficult to compare our model of DNA-ribosome interactions with other physical models of DNA confinement and compaction. The two most recent models treat the DNA polymer as a freely jointed chain of beads (Pelletier et al., 2012; Shendruk et al., 2015), whereas we represent DNA as plectonemes modeled as a hyper-branched chain of sticks connecting beads. The other models include small-protein crowders but not ribosomes, whereas we include ribosomes explicitly and neglect small-protein crowders. With its 7000 connecting rods, our hyper-branched chain has many more internal degrees of freedom than a freely jointed chain of several 100 beads, and so may have a greater tendency to avoid walls. We anticipate more detailed physical models in the future, perhaps including crowders of all sizes, the effects of transertion, and new information about specific DNA conformations from chromosome-capture experiments (
New Evidence for Transertion
Background
Transertion is viewed as a dynamic process in which numerous membrane-DNA linkages are constantly forming and breaking during normal transcription and translation events (Norris and Madsen, 1995). The transertion hypothesis implies DNA-RNAP-mRNA-ribosome-polypeptide-membrane “transertion chains” that tether the chromosomal DNA to the cytoplasmic membrane and provide a radially expanding force on the nucleoids (Figure 1). The primary evidence for transertion had long been the dramatic contraction of the nucleoids after treatment with drugs that halt translation (e.g., chloramphenicol; van Helvoort et al., 1996; Zimmerman, 2002). Such treatment should break the transertion chains on the timescale of completion of transcription events (∼20 s). However, transertion chains should also be broken by drugs such as rifampicin (“Rif”), which prevents transcription initiation. Yet cells observed 20–30 min after Rif treatment showed nucleoid expansion, in contradiction of the transertion hypothesis (
Recent additional support for transertion came from the Goulian lab. Libby et al. (2012), they discovered a net outward migration of genes encoding cytoplasmic membrane proteins within minutes of induction of transcription. They measured the 2D spatial distribution of fluorescent markers of genes encoding two soluble proteins (mcherry, coding the fluorescent protein mCherry; and aadA, spectinomycin adenylyltransferase) and of genes encoding two membrane proteins (lacY, lactose permease; and tetA, the tetracycline efflux pump). For the two membrane-protein genes (but not for the soluble protein genes), induction caused a substantial outward shift in the distribution (toward the membrane), consistent with the transertion hypothesis. The shift occurred within 1–3 min of gene induction.
Short-Time Imaging of Drug Effects on Nucleoid Morphology
Our recent time-resolved drug studies have resolved the Rif dilemma (
A “Transcription-Centric” Model of E. coli Organization
In a separate chapter of this compendium, Ding Jin presents a very different view of the factors governing the overall DNA spatial distribution. The model from the Jin lab might be called “transcription-centric.”
The transcription foci are very likely concentrated centers of transcription of rrn operons, the predominant type of transcription in rapidly growing cells. The seven rrn operons are distributed broadly within the half of the chromosome closest to oriC. Rapidly growing cells containing perhaps four genome equivalents of DNA can easily harbor ∼40 rrn operons, a number that far exceeds the number of transcription foci observed. This strongly suggests clustering of rrn operons into hubs of rRNA transcription, perhaps analogous to the nucleolus of eukaryotic cells. The cause of such clustering is unknown. Cook and co-workers developed a statistical model that suggested that a strong depletion-attraction force would arise between two rrn operons heavily decorated with RNAP copies (Marenduzzo et al., 2006).
Across a variety of growth conditions, mutant strains, and drug treatments,
The most recent concept involves the redistribution of RNAP copies that occurs in conditions that “dissolve” transcription foci. Imaging evidence indicates that the transcription foci tend to lie at or near the nucleoid periphery (
Instead, we believe it is the translational entropy of free ribosomal subunits that drives the expansion of the nucleoid (
It might be suggested that the gathering of multiple rrn operons into a single rrn cluster, whatever the underlying cause, constrains the entire nucleoid to be more compact. A critical test of this suggestion would use dual-color fluorescence reporter–operator systems (FROS) to label two different rrn operons and test whether rrn clusters persist or disperse in slow growth. If they disperse and the nucleoids expand, the idea may have merit. At present, a counter-argument is that the linear contour of one genome measures 1.5 mm in length. Whatever causes rrn operons to cluster, it seems likely to us that there is plenty of “slack” in the overall chromosome to accommodate clustering of distant operons without compacting the overall nucleoid morphology. Additional study of the confined DNA polymer model, including pinning together of distant beads to each other, may be informative here.
Also relevant is a recent study of DAPI-stained nucleoid morphology in different growth conditions (Kuhlman and Cox, 2012). From a quantitative comparison of the integrated curvature of 2D images of the nucleoids, they inferred that the nucleoids are substantially more condensed (have higher density) in slowly growing cells than in rapidly growing cells. Since transcription foci do not occur in slowly growing cells, this would appear to oppose the trend predicted by the transcription-centric model of
We plan to extend our ribosome, RNAP, and nucleoid imaging and tracking studies to very slow growth conditions to test the nucleoid-ribosome mixing hypothesis in a very different physiological context.
Does mRNA Co-localize with Ribosomes or with the Gene from Which it was Transcribed?
According to our model of E. coli spatial organization, in rapid growth most translation is physically separated from most transcription. The exception is the small fraction of co-transcriptional translation (perhaps 10–15%), which should co-localize with the chromosomal DNA. If this picture is essentially correct, then the spatial distribution of total mRNA should mimic that of the ribosomes more closely than that of the chromosomal DNA.
As reviewed by Amster-Choder and co-workers (
Results in Rapidly Growing E. coli and B. subtilis
Early on,
Amster-Choder and co-workers labeled specific E. coli genes in live cells under fast growth conditions using the MS2-GFP procedure (Nevo-Dinur et al., 2011). They found that the mRNA coding for the membrane proteins lacY and bglF was localized at the membrane. This behavior persisted even after treatment with translation-halting drugs such as Cam. The interpretation was that the mRNA itself contains information that targets the transcript to the location where the protein will ultimately be used, analogous to what occurs in eukaryotic cells. However, if the lead ribosome (i.e., the one connected to the RNA polymerase) is indeed necessary to prevent premature intrinsic or Rho-dependent termination of transcription (
In contrast, the mRNAs coding for the cytoplasmic proteins cat and bglB were distributed throughout the cytoplasm in a pattern that was described as helical (Nevo-Dinur et al., 2011). However, to our eyes the cat and bglB mRNA distributions look like the strongly segregated ribosomal spatial distributions in fast growth conditions (Figure 4).
We recently used the fluorescent stain SYTO RNASelect to monitor the degradation of total mRNA following Rif treatment (
Allowing for some re-interpretation of the Amster-Choder results, the available data on mRNA distributions from live, rapidly growing E. coli cells seems quite consistent with our overall picture of strong ribosome-DNA spatial segregation in rapidly growing cells.
Rapidly growing B. subtilis cells also exhibit strong nucleoid-ribosome segregation (Lewis et al., 2000). The first two-color widefield studies of cells with DNA stained and ribosomes labeled showed two or three ribosome-rich regions with interleaved regions of concentrated DNA. We know of no data on mRNA spatial distribution in B. subtilis, but we expect the distribution would closely mimic the ribosome distribution.
Results in Slowly Growing C. crescentus and E. coli
Using FISH in the slowly growing species C. crescentus, the Jacobs-Wagner lab found that six different mRNA messages formed images comprising one or a few puncta (Llopis et al., 2010). Remarkably, each of these puncta co-localized with the corresponding gene (also detected by FISH). In addition, the ribosomes and DNA mix extensively in C. crescentus. The mixing means that there is no contradiction between retention of mRNA near the site of its transcription and repeated translation of the same message. In slowly growing E. coli, similar mRNA and gene co-localization was observed for lacZ. This suggests that in slow growth conditions, mRNA diffusion away from the gene from which it was transcribed is very slow, in contrast to our picture of facile mRNA escape from the nucleoids in rapid growth conditions.
In a similar vein, Kuhlman and Cox (2012) used DAPI staining, “FROS” (a fluorescent reporter–operator system), FISH, and Venus labeling in E. coli to measure the spatial distributions (averaged over many cells) of the overall nucleoid, the lacI gene, its lacI mRNA product, and its LacI-Venus protein product. In slow growth, they varied the position of the lacI gene, either on an extrachromosomal plasmid, near oriC, or near ter. The gene and mRNA distributions are non-uniform and quite different in the three cases, exhibiting two, one, and three axial peaks, respectively. In all three cases, the mRNA distribution closely mimicked the gene distribution, again suggesting that the mRNA is not readily diffusing away from the location where it was transcribed. It is perhaps worth noting that the three different lacI gene and mRNA spatial distributions in slow growth conditions all have strong peaks in locations that would match our three ribosome-rich regions in rapidly growing cells. However, in rapidly growing E. coli, Kuhlman and Cox (2012) found that the lacI mRNA spatial distributions from FISH mimic the overall nucleoid distributions, again suggesting that the mRNA does not readily escape the nucleoids. That is, the lacI mRNA does not form a pattern mimicking the ribosome spatial distributions of Figures 3 and 4.
In slowly growing E. coli the evidence for two different genes (lac Z and lacI) indicates that the corresponding mRNA message remains in the vicinity of the gene itself rather than diffusing away (Kuhlman and Cox, 2012). It is possible that the behavior of lacZ and lacI mRNA in slowly growing cells is somehow not representative of the predominant mRNA behavior. It is also possible that strong DNA-ribosome segregation only occurs in rapidly growing cells. However, facile DNA-ribosome mixing in slow growth would seem contrary to the Kuhlman and Cox (2012) inference of higher DNA density in slowly growing cells than in rapidly growing cells. According to our Monte Carlo modeling, higher DNA density in slowly growing cells would exclude 70S-polysomes to a greater extent, assuming that they can escape the nucleoid interior in the first place.
At present, the mRNA data on slowly growing cells, both E. coli and C. crescentus, stand in opposition to a picture of strong DNA-ribosome segregation and diffusion of free mRNA to ribosome-rich regions where the bulk of translation occurs. We have not carried out detailed super-resolution studies of ribosomes in slowly growing E. coli. We plan to repeat the spatial distribution and diffusion studies to measure the degree of nucleoid-ribosome segregation and the diffusive properties of the ribosomes. Studies of the SYTO RNASelect staining pattern in slow growth are also of interest.
Returning to rapidly growing E. coli cells, it seems highly implausible to us that the nucleoids and ribosomes would be strongly segregated while the overall mRNA spatial distribution would mimic that of the chromosomal DNA. If that were the case, then what are the ∼80% of ribosomes doing while they are so far from the majority of the mRNA that they must translate? The situation could be quite different in slowly growing E. coli. Additional work is needed.
Summary
We have presented a comprehensive model whose goal is to explain the coarse spatial organization of the E. coli transcription and translation machinery in rapid growth conditions with and without the influence of transcription- or translation-halting drugs. This builds on a great deal of earlier work from other labs (Odijk, 1998; Pelletier et al., 2012). Our model takes account of both the biochemical state of the cell (fraction of ribosomes engaged in translation, presence or absence of transertion chains) and the important underlying physical effects of excluded volume and conformational and translational entropy. By treating the ribosomes and DNA as a coupled biochemical–biophysical system, the model explains a wide variety of experimental results.
A wise cell biologist once complained that the trouble with physics-based hypotheses attempting to explain aspects of cellular behavior is that they can never be critically tested. There are no appropriate negative controls—you cannot turn the physics off. Our response would be that neither should the physics be neglected in our thinking. Physical models that make experimentally testable predictions have real value in cell biology. Our physical model can explain why in normal, rapid growth conditions 70S-polysomes and the nucleoids segregate, while free 30S and 50S subunits mix with the nucleoids. The model is oversimplified to be sure, but we believe it captures essential interactions that must not be ignored. From the time-dependent drug studies, we further infer that transertion maintains the nucleoids in a sufficiently expanded state to enable recycling of 30S and 50S subunits between ribosome-rich regions and the nucleoid interior, where they initiate co-transcriptional translation. This in turn protects the nascent mRNA and prevents undesirable backtracking of RNA polymerase.
These concepts suggest how the strongly coupled transcription-translation-transertion system may enhance the maximum growth rate of E. coli. Strong segregation of DNA and RNAP from 70S-polysomes in rapid growth may significantly decrease the search times of RNAP for transcription initiation sites and of free 30S and 50S ribosomal subunits for translation initiation sites. Future work will provide additional quantitative detail in rapid growth and seek a better understanding of the situation in slowly growing cells.
Statements
Acknowledgments
Different aspects of this research were supported by the grants CHE-1213860 from the US National Science Foundation and R01-GM094510 and R01-GM093265 from the National Institutes of Health (NIGMS). We are deeply indebted to our co-workers and collaborators, including Dr. Jagannath Mondal, Prof. Arun Yethiraj, Prof. Mark Goulian, Dr. Albert Siryaporn, Dr. Benjamin Bratton, Dr. Renee Dalrymple, and Ms. Wenting Li.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
single-molecule tracking live cell, E. coli, ribosomes, RNA polymerase, nucleoid structure, DNA-ribosome spatial segregation
Citation
Bakshi S, Choi H and Weisshaar JC (2015) The spatial biology of transcription and translation in rapidly growing Escherichia coli. Front. Microbiol. 6:636. doi: 10.3389/fmicb.2015.00636
Received
30 March 2015
Accepted
12 June 2015
Published
02 July 2015
Volume
6 - 2015
Edited by
Conrad L. Woldringh, University of Amsterdam, Netherlands
Reviewed by
Vic Norris, University of Rouen, France; Suckjoon Jun, University of California, San Diego, USA
Copyright
© 2015 Bakshi, Choi and Weisshaar.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: James C. Weisshaar, Department of Chemistry and Molecular Biophysics Program, University of Wisconsin-Madison, Madison, WI 53706, USA, weisshaar@chem.wisc.edu
†Present address: Somenath Bakshi, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA, somenath_bakshi@hms.harvard.edu
This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology
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