Spatial organization of transcription in bacterial cells

Memory effects of transcription regulator-DNA interactions in bacteria

Memory effect refers to the phenomenon where past events influence a system's current and future states or behaviors. In biology, memory effects often arise from intra- or intermolecular interactions, leading to temporally correlated behaviors. Single-molecule studies have shown that enzymes and DNA-binding proteins can exhibit time-correlated behaviors of their activity. While memory effects are well documented and studied in vitro, no such examples exist in cells to our knowledge. Combining single-molecule tracking (SMT) and single-cell protein quantitation, we find in living Escherichia coli cells distinct temporal correlations in the binding/unbinding events on DNA by MerR- and Fur-family metalloregulators, manifesting as memory effects with timescales of ~1 s. These memory effects persist irrespective of the type of the metalloregulators or their metallation states. Moreover, these temporal correlations of metalloregulator-DNA interactions are associated with spatial confinements of the metalloregulators near their DNA binding sites, suggesting microdomains of ~100 nm in size that possibly result from the spatial organizations of the bacterial chromosome without the involvement of membranes. These microdomains likely facilitate repeated binding events, enhancing regulator-DNA contact frequency and potentially gene regulation efficiency. These findings provide unique insights into the spatiotemporal dynamics of protein-DNA interactions in bacterial cells, introducing the concept of microdomains as a crucial player in memory effect-driven gene regulation.

Analysis of Fluorescent Proteins for Observing Single Gene Locus in a Live and Fixed Escherichia coli Cell

Fluorescent proteins (FPs) are essential tools for advanced microscopy techniques such as super-resolution imaging, single-particle tracking, and quantitative single-molecule counting. Various FPs fused to DNA-binding proteins have been used to observe the subcellular location and movement of specific gene loci in living and fixed bacterial cells. However, quantitative assessments of the properties of FPs for gene locus measurements are still lacking. Here, we assessed various FPs to observe specific gene loci in live and fixed Escherichia coli cells using a fluorescent repressor-operator binding system (FROS), tet operator-Tet repressor proteins (TetR). Tsr-fused FPs were used to assess the intensity and photostability of various FPs (five red FPs: mCherry2, FusionRed, mRFP, mCrimson3, and dKatushka; and seven yellow FPs: SYFP2, Venus, mCitrine, YPet, mClover3, mTopaz, and EYFP) at the single-molecule level in living cells. These FPs were then used for gene locus measurements using FROS. Our results indicate that TetR-mCrimson3 (red) and TetR-EYFP (yellow) had better properties for visualizing gene loci than the other TetR-FPs. Furthermore, fixation procedures affected the clustering of diffusing TetR-FPs and altered the locations of the TetR-FP foci. Fixation with formaldehyde consistently disrupted proper DNA locus observations using TetR-FPs. Notably, the foci measured using TetR-mCrimson3 remained close to their original positions in live cells after glyoxal fixation. This in vivo study provides a cell-imaging guide for the use of FPs for gene-locus observation in E. coli and a scheme for evaluating the use of FPs for other cell-imaging purposes.

Isolation and Partial Characterization of Novel, Structurally Uniform (Hfq6)n≥8 Assemblies Carrying Accessory Transcription and Translation Factors

In growing E. coli cells, the transcription-translation complexes (TTCs) form characteristic foci; however, the exact molecular composition of these superstructures is not known with certainty. Herein, we report that, during our recently developed "fast" procedures for purification of E. coli RNA polymerase (RP), a fraction of the RP's α/RpoA subunits is displaced from the core RP complexes and copurifies with multiprotein superstructures carrying the nucleic acid-binding protein Hfq and the ribosomal protein S6. We show that the main components of these large multiprotein assemblies are fixed protein copy-number (Hfq6)n≥8 complexes; these complexes have a high level of structural uniformity and are distinctly unlike the previously described (Hfq6)n "head-to-tail" polymers. We describe purification of these novel, structurally uniform (Hfq6)n≥8 complexes to near homogeneity and show that they also contain small nonprotein molecules and accessory S6. We demonstrate that Hfq, S6, and RP have similar solubility profiles and present evidence pointing to a role of the Hfq C-termini in superstructure formation. Taken together, our data offer new insights into the composition of the macromolecular assemblies likely acting as scaffolds for transcription complexes and ribosomes during bacterial cells' active growth.

Bacterial nucleoid is a riddle wrapped in a mystery inside an enigma

Bacterial chromosome, the nucleoid, is traditionally modeled as a rosette of DNA mega-loops, organized around proteinaceous central scaffold by nucleoid-associated proteins (NAPs), and mixed with the cytoplasm by transcription and translation. Electron microscopy of fixed cells confirms dispersal of the cloud-like nucleoid within the ribosome-filled cytoplasm. Here, I discuss evidence that the nucleoid in live cells forms DNA phase separate from riboprotein phase, the "riboid." I argue that the nucleoid-riboid interphase, where DNA interacts with NAPs, transcribing RNA polymerases, nascent transcripts, and ssRNA chaperones, forms the transcription zone. An active part of phase separation, transcription zone enforces segregation of the centrally positioned information phase (the nucleoid) from the surrounding action phase (the riboid), where translation happens, protein accumulates, and metabolism occurs. I speculate that HU NAP mostly tiles up the nucleoid periphery-facilitating DNA mobility but also supporting transcription in the interphase. Besides extruding plectonemically supercoiled DNA mega-loops, condensins could compact them into solenoids of uniform rings, while HU could support rigidity and rotation of these DNA rings. The two-phase cytoplasm arrangement allows the bacterial cell to organize the central dogma activities, where (from the cell center to its periphery) DNA replicates and segregates, DNA is transcribed, nascent mRNA is handed over to ribosomes, mRNA is translated into proteins, and finally, the used mRNA is recycled into nucleotides at the inner membrane. The resulting information-action conveyor, with one activity naturally leading to the next one, explains the efficiency of prokaryotic cell design-even though its main intracellular transportation mode is free diffusion.

Targeting bacterial transcription factors for infection control: opportunities and challenges

The rising threat of antibiotic resistance in pathogenic bacteria emphasizes the need for new therapeutic strategies. This review focuses on bacterial transcription factors (TFs), which play crucial roles in bacterial pathogenesis. We discuss the regulatory roles of these factors through examples, and we outline potential therapeutic strategies targeting bacterial TFs. Specifically, we discuss the use of small molecules to interfere with TF function and the development of transcription factor decoys, oligonucleotides that compete with promoters for TF binding. We also cover peptides that target the interaction between the bacterial TF and other factors, such as RNA polymerase, and the targeting of sigma factors. These strategies, while promising, come with challenges, from identifying targets to designing interventions, managing side effects, and accounting for changing bacterial resistance patterns. We also delve into how Artificial Intelligence contributes to these efforts and how it may be exploited in the future, and we touch on the roles of multidisciplinary collaboration and policy to advance this research domain.Abbreviations: AI, artificial intelligence; CNN, convolutional neural networks; DTI: drug-target interaction; HTH, helix-turn-helix; IHF, integration host factor; LTTRs, LysR-type transcriptional regulators; MarR, multiple antibiotic resistance regulator; MRSA, methicillin resistant Staphylococcus aureus; MSA: multiple sequence alignment; NAP, nucleoid-associated protein; PROTACs, proteolysis targeting chimeras; RNAP, RNA polymerase; TF, transcription factor; TFD, transcription factor decoying; TFTRs, TetR-family transcriptional regulators; wHTH, winged helix-turn-helix.

The Operon as a Conundrum of Gene Dynamics and Biochemical Constraints: What We Have Learned from Histidine Biosynthesis

Operons represent one of the leading strategies of gene organization in prokaryotes, having a crucial influence on the regulation of gene expression and on bacterial chromosome organization. However, there is no consensus yet on why, how, and when operons are formed and conserved, and many different theories have been proposed. Histidine biosynthesis is a highly studied metabolic pathway, and many of the models suggested to explain operons origin and evolution can be applied to the histidine pathway, making this route an attractive model for the study of operon evolution. Indeed, the organization of his genes in operons can be due to a progressive clustering of biosynthetic genes during evolution, coupled with a horizontal transfer of these gene clusters. The necessity of physical interactions among the His enzymes could also have had a role in favoring gene closeness, of particular importance in extreme environmental conditions. In addition, the presence in this pathway of paralogous genes, heterodimeric enzymes and complex regulatory networks also support other operon evolution hypotheses. It is possible that histidine biosynthesis, and in general all bacterial operons, may result from a mixture of several models, being shaped by different forces and mechanisms during evolution.

The Spatial Organization of Bacterial Transcriptional Regulatory Networks

The transcriptional regulatory network (TRN) is the central pivot of a prokaryotic organism to receive, process and respond to internal and external environmental information. However, little is known about its spatial organization so far. In recent years, chromatin interaction data of bacteria such as Escherichia coli and Bacillus subtilis have been published, making it possible to study the spatial organization of bacterial transcriptional regulatory networks. By combining TRNs and chromatin interaction data of E. coli and B. subtilis, we explored the spatial organization characteristics of bacterial TRNs in many aspects such as regulation directions (positive and negative), central nodes (hubs, bottlenecks), hierarchical levels (top, middle, bottom) and network motifs (feed-forward loops and single input modules) of the TRNs and found that the bacterial TRNs have a variety of stable spatial organization features under different physiological conditions that may be closely related with biological functions. Our findings provided new insights into the connection between transcriptional regulation and the spatial organization of chromosome in bacteria and might serve as a factual foundation for trying spatial-distance-based gene circuit design in synthetic biology.

The spatial position effect: synthetic biology enters the era of 3D genomics

Microbial cell factories are critical to achieving green biomanufacturing. A position effect occurs when a synthetic gene circuit is expressed from different positions in the chassis strain genome. Here, we propose the concept of the 'spatial position effect,' which uses technologies in 3D genomics to reveal the spatial structure characteristics of the 3D genome of the chassis. On this basis, we propose to rationally design the integration sites of synthetic gene circuits, use reporter genes for preliminary screening, and integrate synthetic gene circuits into promising sites for further experiments. This approach can produce stable and efficient chassis strains for green biomanufacturing. The proposed spatial position effect brings synthetic biology into the era of 3D genomics.

Generating Chromosome Geometries in a Minimal Cell From Cryo-Electron Tomograms and Chromosome Conformation Capture Maps

JCVI-syn3A is a genetically minimal bacterial cell, consisting of 493 genes and only a single 543 kbp circular chromosome. Syn3A’s genome and physical size are approximately one-tenth those of the model bacterial organism Escherichia coli’s, and the corresponding reduction in complexity and scale provides a unique opportunity for whole-cell modeling. Previous work established genome-scale gene essentiality and proteomics data along with its essential metabolic network and a kinetic model of genetic information processing. In addition to that information, whole-cell, spatially-resolved kinetic models require cellular architecture, including spatial distributions of ribosomes and the circular chromosome’s configuration. We reconstruct cellular architectures of Syn3A cells at the single-cell level directly from cryo-electron tomograms, including the ribosome distributions. We present a method of generating self-avoiding circular chromosome configurations in a lattice model with a resolution of 11.8 bp per monomer on a 4 nm cubic lattice. Realizations of the chromosome configurations are constrained by the ribosomes and geometry reconstructed from the tomograms and include DNA loops suggested by experimental chromosome conformation capture (3C) maps. Using ensembles of simulated chromosome configurations we predict chromosome contact maps for Syn3A cells at resolutions of 250 bp and greater and compare them to the experimental maps. Additionally, the spatial distributions of ribosomes and the DNA-crowding resulting from the individual chromosome configurations can be used to identify macromolecular structures formed from ribosomes and DNA, such as polysomes and expressomes.

A plant CitPITP1 protein-coding exon sequence serves as a promoter in bacteria

Genetic manipulation of plant genes in prokaryotes has been widely used in molecular biology, but the function of a DNA sequence is far from being fully known. Here, we discovered that a plant protein-coding gene containing the CRAL_TRIO domain serves as a promoter in bacteria. We firstly characterized CitPITP1 from Citrus, which contains the CRAL_TRIO domain, and identified a 64-bp sequence (key64) that is critical for prokaryotic promoter activity. In vitro experiments indicated that the bacterial RNA polymerase subunit RpoD specifically binds to key64. We then expanded our research to fungi, plant and animal species to identify key64-like sequences. Five such prokaryotic promoters were isolated from Amborella, Rice, Arabidopsis and Citrus. Two conserved motifs were identified, and mutation analysis indicated that the nucleotides at positions 7, 29 and 30 are crucial for key64-like transcription activity. We detected full-length recombinant CitPITP1 from E. coli, and visualized a CitPITP1-GFP fusion protein in plant cells, supporting the idea that CitPITP1 encodes a protein. However, although exon 4 of CitPITP1 contained key64, it did not demonstrate promoter activity in plants. Our study describes a new basal promoter, provides evidence for neofunction of gene elements across different kingdoms, and provides new knowledge for the modular design of promoters.

A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM

Single-molecule localization microscopy (SMLM) relies on the blinking behavior of a fluorophore, which is the stochastic switching between fluorescent and dark states. Blinking creates multiple localizations belonging to the same fluorophore, confounding quantitative analyses and interpretations. Here we present a method, termed distance distribution correction (DDC), to eliminate blinking-caused repeat localizations without any additional calibrations. The approach relies on obtaining the true pairwise distance distribution of different fluorophores naturally from the imaging sequence by using distances between localizations separated by a time much longer than the average fluorescence survival time. We show that, using the true pairwise distribution, we can define and maximize the likelihood, obtaining a set of localizations void of blinking artifacts. DDC results in drastic improvements in obtaining the closest estimate of the true spatial organization and number of fluorescent emitters in a wide range of applications, enabling accurate reconstruction and quantification of SMLM images.

A pairwise distance distribution correction (DDC) algorithm to eliminate blinking-caused artifacts in SMLM

Single-molecule localization microscopy (SMLM) relies on the blinking behavior of a fluorophore, which is the stochastic switching between fluorescent and dark states. Blinking creates multiple localizations belonging to the same fluorophore, confounding quantitative analyses and interpretations. Here we present a method, termed distance distribution correction (DDC), to eliminate blinking-caused repeat localizations without any additional calibrations. The approach relies on obtaining the true pairwise distance distribution of different fluorophores naturally from the imaging sequence by using distances between localizations separated by a time much longer than the average fluorescence survival time. We show that, using the true pairwise distribution, we can define and maximize the likelihood, obtaining a set of localizations void of blinking artifacts. DDC results in drastic improvements in obtaining the closest estimate of the true spatial organization and number of fluorescent emitters in a wide range of applications, enabling accurate reconstruction and quantification of SMLM images.

Whole genome strategies and bioremediation insight into dehalogenase-producing bacteria

An integral approach to decoding both culturable and uncultured microorganisms' metabolic activity involves the whole genome sequencing (WGS) of individual/complex microbial communities. WGS of culturable microbes, amplicon sequencing, metagenomics, and single-cell genome analysis are selective techniques integrating genetic information and biochemical mechanisms. These approaches transform microbial biotechnology into a quick and high-throughput culture-independent evaluation and exploit pollutant-degrading microbes. They are windows into enzyme regulatory bioremediation pathways (i.e., dehalogenase) and the complete bioremediation process of organohalide pollutants. While the genome sequencing technique is gaining the scientific community's interest, it is still in its infancy in the field of pollutant bioremediation. The techniques are becoming increasingly helpful in unraveling and predicting the enzyme structure and explore metabolic and biodegradation capabilities.

Transcriptional regulation of organohalide pollutant utilisation in bacteria

Organohalides are organic molecules formed biotically and abiotically, both naturally and through industrial production. They are usually toxic and represent a health risk for living organisms, including humans. Bacteria capable of degrading organohalides for growth express dehalogenase genes encoding enzymes that cleave carbon-halogen bonds. Such bacteria are of potential high interest for bioremediation of contaminated sites. Dehalogenase genes are often part of gene clusters that may include regulators, accessory genes and genes for transporters and other enzymes of organohalide degradation pathways. Organohalides and their degradation products affect the activity of regulatory factors, and extensive genome-wide modulation of gene expression helps dehalogenating bacteria to cope with stresses associated with dehalogenation, such as intracellular increase of halides, dehalogenase-dependent acid production, organohalide toxicity and misrouting and bottlenecks in metabolic fluxes. This review focuses on transcriptional regulation of gene clusters for dehalogenation in bacteria, as studied in laboratory experiments and in situ. The diversity in gene content, organization and regulation of such gene clusters is highlighted for representative organohalide-degrading bacteria. Selected examples illustrate a key, overlooked role of regulatory processes, often strain-specific, for efficient dehalogenation and productive growth in presence of organohalides.

Elucidating the Influence of Chromosomal Architecture on Transcriptional Regulation in Prokaryotes - Observing Strong Local Effects of Nucleoid Structure on Gene Regulation

Both intrinsic and extrinsic mechanisms regulating bacterial expression have been elucidated and described, however, such studies have mainly focused on local effects on the two-dimensional structure of the prokaryote genome while long-range as well as spatial interactions influencing gene expression are still only poorly understood. In this paper, we investigate the association between co-expression and distance between genes, using RNA-seq data at multiple growth phases in order to illuminate whether such conserved patterns are an indication of a gene regulatory mechanism relevant for prokaryotic cell proliferation, adaption, and evolution. We observe recurrent sinusoidal patterns in correlation of pairwise expression as function of genomic distance and rule out that these are caused by transcription-induced supercoiling gradients, gene clustering in operons, or association with regulatory transcription factors (TFs). By comparing spatial proximity for pairs of genomic bins with their correlation of pairwise expression, we further observe a high co-expression proportional with the spatial proximity. Based on these observations, we propose that the observed patterns are related to nucleoid structure as a product of transcriptional spilling, where genes actively influence transcription of spatially proximal genes through increases within shared local pools of RNA polymerases (RNAP), and actively spilling transcription onto neighboring genes.

Effects of spatial heterogeneity on bacterial genetic circuits

Intracellular spatial heterogeneity is frequently observed in bacteria, where the chromosome occupies part of the cell's volume and a circuit's DNA often localizes within the cell. How this heterogeneity affects core processes and genetic circuits is still poorly understood. In fact, commonly used ordinary differential equation (ODE) models of genetic circuits assume a well-mixed ensemble of molecules and, as such, do not capture spatial aspects. Reaction-diffusion partial differential equation (PDE) models have been only occasionally used since they are difficult to integrate and do not provide mechanistic understanding of the effects of spatial heterogeneity. In this paper, we derive a reduced ODE model that captures spatial effects, yet has the same dimension as commonly used well-mixed models. In particular, the only difference with respect to a well-mixed ODE model is that the association rate constant of binding reactions is multiplied by a coefficient, which we refer to as the binding correction factor (BCF). The BCF depends on the size of interacting molecules and on their location when fixed in space and it is equal to unity in a well-mixed ODE model. The BCF can be used to investigate how spatial heterogeneity affects the behavior of core processes and genetic circuits. Specifically, our reduced model indicates that transcription and its regulation are more effective for genes located at the cell poles than for genes located on the chromosome. The extent of these effects depends on the value of the BCF, which we found to be close to unity. For translation, the value of the BCF is always greater than unity, it increases with mRNA size, and, with biologically relevant parameters, is substantially larger than unity. Our model has broad validity, has the same dimension as a well-mixed model, yet it incorporates spatial heterogeneity. This simple-to-use model can be used to both analyze and design genetic circuits while accounting for spatial intracellular effects.

Super-resolution microscopy reveals how histone tail acetylation affects DNA compaction within nucleosomes in vivo

Chromatin organization is crucial for regulating gene expression. Previously, we showed that nucleosomes form groups, termed clutches. Clutch size correlated with the pluripotency grade of mouse embryonic stem cells and human induced pluripotent stem cells. Recently, it was also shown that regions of the chromatin containing activating epigenetic marks were composed of small and dispersed chromatin nanodomains with lower DNA density compared to the larger silenced domains. Overall, these results suggest that clutch size may regulate DNA packing density and gene activity. To directly test this model, we carried out 3D, two-color super-resolution microscopy of histones and DNA with and without increased histone tail acetylation. Our results showed that lower percentage of DNA was associated with nucleosome clutches in hyperacetylated cells. We further showed that the radius and compaction level of clutch-associated DNA decreased in hyperacetylated cells, especially in regions containing several neighboring clutches. Importantly, this change was independent of clutch size but dependent on the acetylation state of the clutch. Our results directly link the epigenetic state of nucleosome clutches to their DNA packing density. Our results further provide in vivo support to previous in vitro models that showed a disruption of nucleosome-DNA interactions upon hyperacetylation.

Transcription and translation contribute to gene locus relocation to the nucleoid periphery in E. coli

Transcription by RNA polymerase (RNAP) is coupled with translation in bacteria. Here, we observe the dynamics of transcription and subcellular localization of a specific gene locus (encoding a non-membrane protein) in living E. coli cells at subdiffraction-limit resolution. The movement of the gene locus to the nucleoid periphery correlates with transcription, driven by either E. coli RNAP or T7 RNAP, and the effect is potentiated by translation.

EVR: reconstruction of bacterial chromosome 3D structure models using error-vector resultant algorithm

BACKGROUND

More and more 3C/Hi-C experiments on prokaryotes have been published. However, most of the published modeling tools for chromosome 3D structures are targeting at eukaryotes. How to transform prokaryotic experimental chromosome interaction data into spatial structure models is an important task and in great need.

RESULTS

We have developed a new reconstruction program for bacterial chromosome 3D structure models called EVR that exploits a simple Error-Vector Resultant (EVR) algorithm. This software tool is particularly optimized for the closed-loop structural features of prokaryotic chromosomes. The parallel implementation of the program can utilize the computing power of both multi-core CPUs and GPUs.

CONCLUSIONS

EVR can be used to reconstruct the bacterial 3D chromosome structure based on the contact frequency matrix derived from 3C/Hi-C experimental data quickly and precisely.

Spatial organization of RNA polymerase and its relationship with transcription in Escherichia coli

Recent studies have shown that RNA polymerase (RNAP) is organized into distinct clusters in Escherichia coli and Bacillus subtilis cells. Spatially organized molecular components in prokaryotic systems imply compartmentalization without the use of membranes, which may offer insights into unique functions and regulations. It has been proposed that the formation of RNAP clusters is driven by active ribosomal RNA (rRNA) transcription and that RNAP clusters function as factories for highly efficient transcription. In this work, we examined these hypotheses by investigating the spatial organization and transcription activity of RNAP in E. coli cells using quantitative superresolution imaging coupled with genetic and biochemical assays. We observed that RNAP formed distinct clusters that were engaged in active rRNA synthesis under a rich medium growth condition. Surprisingly, a large fraction of RNAP clusters persisted in the absence of high rRNA transcription activities or when the housekeeping σ⁷⁰ was sequestered, and was only significantly diminished when all RNA transcription was inhibited globally. In contrast, the cellular distribution of RNAP closely followed the morphology of the underlying nucleoid under all conditions tested irrespective of the corresponding transcription activity, and RNAP redistributed into dispersed, smaller clusters when the supercoiling state of the nucleoid was perturbed. These results suggest that RNAP was organized into active transcription centers under the rich medium growth condition; its spatial arrangement at the cellular level, however, was not dependent on rRNA synthesis activity and was likely organized by the underlying nucleoid.

Role of confinement, molecular connectivity and flexibility in entropic driven surface segregation of polymer-colloid mixtures

Relative surface affinity between polymers and colloids is leveraged in many applications like filtration, adhesion, bio-sensing, etc. The surface affinity is governed by both enthalpic (relative interactions between the species and surface) and entropic (excluded volume) effects. Neglecting enthalpic effects, i.e. for purely athermal systems, entropy is the only driving force that controls the surface affinity of the species in a binary or multi-component mixture. Many intensive (relative size of colloids, chain length, equilibrium bond angle, chain flexibility) and extensive (confinement, temperature) factors can dramatically change the entropy of the system and thus enhance or decrease the surface affinities of the constituent species. In this article, we use coarse grained metropolis Monte Carlo simulations to delineate the role of these factors in entropic surface segregation in a binary mixture of polymers and colloids. At low number densities, excluded volume effects are negligible and we do not observe any entropic driven surface segregation. Therefore our system of interest is binary polymer-colloid mixtures at moderate to high number densities where excluded volume effects are predominant. Our results indicate that for flexible polymer chains, the surface is always enriched with colloids compared to polymers and this effect is enhanced for longer polymer chains. The configurational entropy of the flexible polymers is significantly reduced near the surface and therefore they prefer to stay in the bulk (away from the surface). However this behavior can be completely reversed by introducing a large degree of confinement and making the chains relatively rigid (less flexible). Our results show that polymer segregation of long stiff chains in slit pore geometry is driven by nematization near the surface while looping of polymers is observed under a large degree of confinement. We observe that for longer polymer chains with an equilibrium bond angle (θ = π), both confinement and chain stiffness enhance the surface segregation of polymers relative to colloids. However, the segregation behavior within a confinement is dependent on the polymer chain length. The surface segregation of polymers is dramatically decreased for chains with equilibrium bond angles independent of chain length and flexibility due to excluded volume effects and inefficient packing near the surface.

High-resolution 3D models of Caulobacter crescentus chromosome reveal genome structural variability and organization

High-resolution three-dimensional models of Caulobacter crescentus nucleoid structures were generated via a multi-scale modeling protocol. Models were built as a plectonemically supercoiled circular DNA and by incorporating chromosome conformation capture based data to generate an ensemble of base pair resolution models consistent with the experimental data. Significant structural variability was found with different degrees of bending and twisting but with overall similar topologies and shapes that are consistent with C. crescentus cell dimensions. The models allowed a direct mapping of the genomic sequence onto the three-dimensional nucleoid structures. Distinct spatial distributions were found for several genomic elements such as AT-rich sequence elements where nucleoid associated proteins (NAPs) are likely to bind, promoter sites, and some genes with common cellular functions. These findings shed light on the correlation between the spatial organization of the genome and biological functions.

A Single-Molecule View of Archaeal Transcription

The discovery of the archaeal domain of life is tightly connected to an in-depth analysis of the prokaryotic RNA world. In addition to Carl Woese's approach to use the sequence of the 16S rRNA gene as phylogenetic marker, the finding of Karl Stetter and Wolfram Zillig that archaeal RNA polymerases (RNAPs) were nothing like the bacterial RNAP but are more complex enzymes that resemble the eukaryotic RNAPII was one of the key findings supporting the idea that archaea constitute the third major branch on the tree of life. This breakthrough in transcriptional research 40years ago paved the way for in-depth studies of the transcription machinery in archaea. However, although the archaeal RNAP and the basal transcription factors that fine-tune the activity of the RNAP during the transcription cycle are long known, we still lack information concerning the architecture and dynamics of archaeal transcription complexes. In this context, single-molecule measurements were instrumental as they provided crucial insights into the process of transcription initiation, the architecture of the initiation complex and the dynamics of mobile elements of the RNAP. In this review, we discuss single-molecule approaches suitable to examine molecular mechanisms of transcription and highlight findings that shaped our understanding of the archaeal transcription apparatus. We furthermore explore the possibilities and challenges of next-generation single-molecule techniques, for example, super-resolution microscopy and single-molecule tracking, and ask whether these approaches will ultimately allow us to investigate archaeal transcription in vivo.

Growth phase-specific changes in the composition of E. coli transcription complexes

In E. coli, a single oligomeric enzyme transcribes the genomic DNA, while multiple auxiliary proteins and regulatory RNA interact with the core RNA polymerase (RP) during different stages of the transcription cycle to influence its function. In this work, using fast protein isolation techniques combined with mass spectrometry (MS) and immuno-analyses, we studied growth phase-specific changes in the composition of E. coli transcription complexes. We show that RP isolated from actively growing cells is represented by prevalent double copy assemblies and single copy RP-RNA and RP-RNA-RapA complexes. We demonstrate that RpoD/σ⁷⁰ obtained in fast purification protocols carries tightly associated RNA and show evidence pointing to a role of sigma-associated RNA in the formation of native RP-(RNA)-RpoD/σ⁷⁰ (holoenzyme) complexes. We report that enzymes linked functionally to the metabolism of lipopolysaccharides co-purify with RP-RNA complexes and describe two classes of RP-associated molecules (phospholipids and putative phospholipid-rNT species). We hypothesize that these modifications could enable anchoring of RP-RNA and RNA in cell membranes. We also report that proteins loosely associated with ribosomes and degradosomes (S1, Hfq) co-purify with RP-RNA complexes isolated from actively growing cells - a result consistent with their proposed roles as adaptor-proteins. In contrast, GroEL, SecB, and SecA co-purified with RP obtained from cells harvested in early stationary phase. Our results demonstrate that fast, affinity chromatography-based isolation of large multi-protein assemblies in combination with MS can be used as a tool for analysis of their composition and the profiling of small protein-associated molecules (SPAM).

Genome-wide analysis of fitness data and its application to improve metabolic models

Background

Synthetic biology and related techniques enable genome scale high-throughput investigation of the effect on organism fitness of different gene knock-downs/outs and of other modifications of genomic sequence.

Results

We develop statistical and computational pipelines and frameworks for analyzing high throughput fitness data over a genome scale set of sequence variants. Analyzing data from a high-throughput knock-down/knock-out bacterial study, we investigate differences and determinants of the effect on fitness in different conditions. Comparing fitness vectors of genes, across tens of conditions, we observe that fitness consequences strongly depend on genomic location and more weakly depend on gene sequence similarity and on functional relationships. In analyzing promoter sequences, we identified motifs associated with conditions studied in bacterial media such as Casaminos, D-glucose, Sucrose, and other sugars and amino-acid sources.

We also use fitness data to infer genes associated with orphan metabolic reactions in the iJO1366 E. coli metabolic model. To do this, we developed a new computational method that integrates gene fitness and gene expression profiles within a given reaction network neighborhood to associate this reaction with a set of genes that potentially encode the catalyzing proteins. We then apply this approach to predict candidate genes for 107 orphan reactions in iJO1366. Furthermore - we validate our methodology with known reactions using a leave-one-out approach. Specifically, using top-20 candidates selected based on combined fitness and expression datasets, we correctly reconstruct 39.7% of the reactions, as compared to 33% based on fitness and to 26% based on expression separately, and to 4.02% as a random baseline. Our model improvement results include a novel association of a gene to an orphan cytosine nucleosidation reaction.

Conclusion

Our pipeline for metabolic modeling shows a clear benefit of using fitness data for predicting genes of orphan reactions. Along with the analysis pipelines we developed, it can be used to analyze similar high-throughput data.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2341-9) contains supplementary material, which is available to authorized users.

The transcription-repair coupling factor Mfd associates with RNA polymerase in the absence of exogenous damage

During transcription elongation, bacterial RNA polymerase (RNAP) can pause, backtrack or stall when transcribing template DNA. Stalled transcription elongation complexes at sites of bulky lesions can be rescued by the transcription terminator Mfd. The molecular mechanisms of Mfd recruitment to transcription complexes in vivo remain to be elucidated, however. Using single-molecule live-cell imaging, we show that Mfd associates with elongation transcription complexes even in the absence of exogenous genotoxic stresses. This interaction requires an intact RNA polymerase-interacting domain of Mfd. In the presence of drugs that stall RNAP, we find that Mfd associates pervasively with RNAP. The residence time of Mfd foci reduces from 30 to 18 s in the presence of endogenous UvrA, suggesting that UvrA promotes the resolution of Mfd-RNAP complexes on DNA. Our results reveal that RNAP is frequently rescued by Mfd during normal growth and highlight a ubiquitous house-keeping role for Mfd in regulating transcription elongation.

The Divided Bacterial Genome: Structure, Function, and Evolution

Approximately 10% of bacterial genomes are split between two or more large DNA fragments, a genome architecture referred to as a multipartite genome. This multipartite organization is found in many important organisms, including plant symbionts, such as the nitrogen-fixing rhizobia, and plant, animal, and human pathogens, including the genera Brucella, Vibrio, and Burkholderia. The availability of many complete bacterial genome sequences means that we can now examine on a broad scale the characteristics of the different types of DNA molecules in a genome. Recent work has begun to shed light on the unique properties of each class of replicon, the unique functional role of chromosomal and nonchromosomal DNA molecules, and how the exploitation of novel niches may have driven the evolution of the multipartite genome. The aims of this review are to (i) outline the literature regarding bacterial genomes that are divided into multiple fragments, (ii) provide a meta-analysis of completed bacterial genomes from 1,708 species as a way of reviewing the abundant information present in these genome sequences, and (iii) provide an encompassing model to explain the evolution and function of the multipartite genome structure. This review covers, among other topics, salient genome terminology; mechanisms of multipartite genome formation; the phylogenetic distribution of multipartite genomes; how each part of a genome differs with respect to genomic signatures, genetic variability, and gene functional annotation; how each DNA molecule may interact; as well as the costs and benefits of this genome structure.

Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria

Small non-coding RNAs can exert significant regulatory activity on gene expression in bacteria. In recent years, substantial progress has been made in understanding bacterial gene expression by sRNAs. However, recent findings that demonstrate that families of mRNAs show non-trivial sub-cellular distributions raise the question of how localization may affect the regulatory activity of sRNAs. Here we address this question within a simple mathematical model. We show that the non-uniform spatial distributions of mRNA can alter the threshold-linear response that characterizes sRNAs that act stoichiometrically, and modulate the hierarchy among targets co-regulated by the same sRNA. We also identify conditions where the sub-cellular organization of cofactors in the sRNA pathway can induce spatial heterogeneity on sRNA targets. Our results suggest that under certain conditions, interpretation and modeling of natural and synthetic gene regulatory circuits need to take into account the spatial organization of the transcripts of participating genes.

Deconvolution of Gene Expression Noise into Spatial Dynamics of Transcription Factor-Promoter Interplay

Gene expression noise is not only the mere consequence of stochasticity, but also a signal that reflects the upstream physical dynamics of the cognate molecular machinery. Soil bacteria facing recalcitrant pollutants exploit noise of catabolic promoters to deploy beneficial phenotypes such as metabolic bet-hedging and/or division of biochemical labor. Although the role of upstream promoter-regulator interplay in the origin of this noise is little understood, its specifications are probably ciphered in flow cytometry data patterns. We studied Pm promoter activity of the environmental bacterium Pseudomonas putida and its cognate regulator XylS by following expression of Pm-gfp fusions in single cells. Using mathematical modeling and computational simulations, we determined the kinetic properties of the system and used them as a baseline code to interpret promoter activity in terms of upstream regulator dynamics. Transcriptional noise was predicted to depend on the intracellular physical distance between regulator source (where XylS is produced) and the target promoter. Experiments with engineered bacteria in which this distance is minimized or enlarged confirmed the predicted effects of source/target proximity on noise patterns. This approach allowed deconvolution of cytometry data into mechanistic information on gene expression flow. It also provided a basis for selecting programmable noise levels in synthetic regulatory circuits.

Use of small-angle X-ray scattering to resolve intracellular structure changes of Escherichia coli cells induced by antibiotic treatment

The application of small-angle X-ray scattering (SAXS) to whole Escherichia coli cells is challenging owing to the variety of internal constituents. To resolve their contributions, the outer shape was captured by ultra-small-angle X-ray scattering and combined with the internal structure resolved by SAXS. Building on these data, a model for the major structural components of E. coli was developed. It was possible to deduce information on the occupied volume, occurrence and average size of the most important intracellular constituents: ribosomes, DNA and proteins. E. coli was studied after treatment with three different antibiotic agents (chloramphenicol, tetracycline and rifampicin) and the impact on the intracellular constituents was monitored.

CRISPR technologies for bacterial systems: Current achievements and future directions

Throughout the decades of its history, the advances in bacteria-based bio-industries have coincided with great leaps in strain engineering technologies. Recently unveiled clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) systems are now revolutionizing biotechnology as well as biology. Diverse technologies have been derived from CRISPR/Cas systems in bacteria, yet the applications unfortunately have not been actively employed in bacteria as extensively as in eukaryotic organisms. A recent trend of engineering less explored strains in industrial microbiology-metabolic engineering, synthetic biology, and other related disciplines-is demanding facile yet robust tools, and various CRISPR technologies have potential to cater to the demands. Here, we briefly review the science in CRISPR/Cas systems and the milestone inventions that enabled numerous CRISPR technologies. Next, we describe CRISPR/Cas-derived technologies for bacterial strain development, including genome editing and gene expression regulation applications. Then, other CRISPR technologies possessing great potential for industrial applications are described, including typing and tracking of bacterial strains, virome identification, vaccination of bacteria, and advanced antimicrobial approaches. For each application, we note our suggestions for additional improvements as well. In the same context, replication of CRISPR/Cas-based chromosome imaging technologies developed originally in eukaryotic systems is introduced with its potential impact on studying bacterial chromosomal dynamics. Also, the current patent status of CRISPR technologies is reviewed. Finally, we provide some insights to the future of CRISPR technologies for bacterial systems by proposing complementary techniques to be developed for the use of CRISPR technologies in even wider range of applications.

Analysis tools for the interplay between genome layout and regulation

BACKGROUND

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes.

RESULTS

Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation.

GREAT

SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information.

CONCLUSIONS

We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

Comparative Genomics of Interreplichore Translocations in Bacteria: A Measure of Chromosome Topology?

Genomes evolve not only in base sequence but also in terms of their architecture, defined by gene organization and chromosome topology. Whereas genome sequence data inform us about the changes in base sequences for a large variety of organisms, the study of chromosome topology is restricted to a few model organisms studied using microscopy and chromosome conformation capture techniques. Here, we exploit whole genome sequence data to study the link between gene organization and chromosome topology in bacteria. Using comparative genomics across ∼250 pairs of closely related bacteria we show that: (a) many organisms show a high degree of interreplichore translocations throughout the chromosome and not limited to the inversion-prone terminus (ter) or the origin of replication (oriC); (b) translocation maps may reflect chromosome topologies; and (c) symmetric interreplichore translocations do not disrupt the distance of a gene from oriC or affect gene expression states or strand biases in gene densities. In summary, we suggest that translocation maps might be a first line in defining a gross chromosome topology given a pair of closely related genome sequences.

GREAT: a web portal for Genome Regulatory Architecture Tools

GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading.

Space-induced bifurcation in repression-based transcriptional circuits

BACKGROUND

Albeit the molecular mechanisms of gene expression are well documented, our understanding of their dynamics is much less advanced. Recent experimental evidence has revealed that gene expression might be accurately organized in space, with several molecular actors localized to specific positions in the cell. However, the influence of this spatial localization on the dynamics of gene expression is unclear. This issue is also central in synthetic biology, where one usually considers the spatial localization in the cell of the genes of the inserted synthetic construct as irrelevant for its temporal dynamics.

RESULTS

Here, we assessed the influence of the spatial distribution of the genes on the dynamics of 3-gene transcriptional ring networks regulated by repression, i.e. repressilator circuits, using individual-based modelling to simulate their dynamics in two and three space dimensions. Our simulations suggest that variations of spatial parameters - namely the degree of demixing of the positions of the gene or the spatial range of the mRNA and proteins (i.e. the typical distance they travel before degradation) - have dramatic effects by switching the dynamical regime from spontaneous oscillations to a stationary state where each species fluctuates around a constant value. By analogy with the bifurcations arising from the variation of kinetic parameters, we referred to those transitions as space-induced bifurcations.

CONCLUSIONS

Taken together, our results strongly support the idea that the spatial organization of the molecular actors of transcriptional networks is crucial for the dynamics of gene expression and suggest that the spatial localization of the synthetic genes in the cell could be used as an additional toggle to control the dynamics of the inserted construct in synthetic biology experiments.