Nucleoid and cytoplasmic localization of small RNAs in Escherichia coli.

Bacterial small RNAs (sRNAs) regulate protein production by binding to mRNAs and altering their translation and degradation. sRNAs are smaller than most mRNAs but larger than many proteins. Therefore it is uncertain whether sRNAs can enter the nucleoid to target nascent mRNAs. Here, we investigate the intracellular localization of sRNAs transcribed from plasmids in Escherichia coli using RNA fluorescent in-situ hybridization. We found that sRNAs (GlmZ, OxyS, RyhB and SgrS) have equal preference for the nucleoid and cytoplasm, and no preferential localization at the cell membrane. We show using the gfp mRNA (encoding green fluorescent protein) that non-sRNAs can be engineered to have different proportions of nucleoid and cytoplasmic localization by altering their length and/or translation. The same localization as sRNAs was achieved by decreasing gfp mRNA length and translation, which suggests that sRNAs and other RNAs may enter the densely packed DNA of the nucleoid if they are sufficiently small. We also found that the Hfq protein, which binds sRNAs, minimally affects sRNA localization. Important implications of our findings for engineering synthetic circuits are: (i) sRNAs can potentially bind nascent mRNAs in the nucleoid, and (ii) localization patterns and distribution volumes of sRNAs can differ from some larger RNAs.

Horizontal transfer of DNA methylation patterns into bacterial chromosomes.

Horizontal gene transfer (HGT) is the non-inherited acquisition of novel DNA sequences. HGT is common and important in bacteria because it enables the rapid generation of new phenotypes such as antibiotic resistance. Here we show that in vivo and in vitro DNA methylation patterns can be horizontally transferred into bacterial chromosomes to program cell phenotypes. The experiments were performed using a synthetic system in Escherichia coli where different DNA methylation patterns within the cis-regulatory sequence of the agn43 gene turn on or off a fluorescent reporter (CFP). With this system we demonstrated that DNA methylation patterns not only accompany the horizontal transfer of genes into the bacterial cytoplasm but can be transferred into chromosomes by: (i) bacteriophage P1 transduction; and (ii) transformation of extracellular synthetic DNA. We also modified the experimental system by replacing CFP with the SgrS small RNA, which regulates glucose and methyl α-D-glucoside uptake, and showed that horizontally acquired DNA methylation patterns can increase or decrease cell fitness. That is, horizontally acquired DNA methylation patterns can result in the selection for and against cells that have HGT. Findings from these proof-of-concept experiments have applications in synthetic biology and potentially broad implications for bacterial adaptation and evolution.

Paradoxical suppression of small RNA activity at high Hfq concentrations due to random-order binding.

Small RNAs (sRNAs) are important regulators of gene expression during bacterial stress and pathogenesis. sRNAs act by forming duplexes with mRNAs to alter their translation and degradation. In some bacteria, duplex formation is mediated by the Hfq protein, which can bind the sRNA and mRNA in each pair in a random order. Here we investigate the consequences of this random-order binding and experimentally demonstrate that it can counterintuitively cause high Hfq concentrations to suppress rather than promote sRNA activity in Escherichia coli. As a result, maximum sRNA activity occurs when the Hfq concentration is neither too low nor too high relative to the sRNA and mRNA concentrations ('Hfq set-point'). We further show with models and experiments that random-order binding combined with the formation of a dead-end mRNA-Hfq complex causes high concentrations of an mRNA to inhibit its own duplex formation by sequestering Hfq. In such cases, maximum sRNA activity requires an optimal mRNA concentration ('mRNA set-point') as well as an optimal Hfq concentration. The Hfq and mRNA set-points generate novel regulatory properties that can be harnessed by native and synthetic gene circuits to provide greater control over sRNA activity, generate non-monotonic responses and enhance the robustness of expression.

Quantitative characterization of gene regulation by Rho dependent transcription termination.

Rho factor dependent transcription termination (RTT) is common within the coding sequences of bacterial genes and it acts to couple transcription and translation levels. Despite the importance of RTT for gene regulation, its effects on mRNA and protein concentrations have not been quantitatively characterized. Here we demonstrate that the exogenous cfp gene encoding the cyan fluorescent protein can serve as a model for gene regulation by RTT. This was confirmed by showing that Psu and bicyclomycin decrease RTT and increase full length cfp mRNAs (but remarkably they have little effect on protein production). We then use cfp to characterize the relationship between its protein and full length mRNA concentrations when the translation initiation rate is varied by sequence modifications of the translation initiation region (TIR). These experiments reveal that the fold change in protein concentration (RP) and the fold change in full length mRNA concentration (Rm) have the relationship RP≈Rm(b), where b is a constant. The average value of b was determined from three separate data sets to be ~3.6. We demonstrate that the above power law function can predict how altering the translation initiation rate of a gene in an operon will affect the mRNA concentrations of downstream genes and specify a lower bound for the associated changes in protein concentrations. In summary, this study defines a simple phenomenological model to help program expression from single genes and operons that are regulated by RTT, and to guide molecular models of RTT.

Rapid and robust signaling in the CsrA cascade via RNA-protein interactions and feedback regulation.

Bacterial survival requires the rapid propagation of signals through gene networks during stress, but how this is achieved is not well understood. This study systematically characterizes the signaling dynamics of a cascade of RNA-protein interactions in the CsrA system, which regulates stress responses and biofilm formation in Escherichia coli. Noncoding RNAs are at the center of the CsrA system; target mRNAs are bound by CsrA proteins that inhibit their translation, CsrA proteins are sequestered by CsrB noncoding RNAs, and the degradation of CsrB RNAs is increased by CsrD proteins. Here, we show using in vivo experiments and quantitative modeling that the CsrA system integrates three strategies to achieve rapid and robust signaling. These strategies include: (i) the sequestration of stable proteins by noncoding RNAs, which rapidly inactivates protein activity; (ii) the degradation of stable noncoding RNAs, which enables their rapid removal; and (iii) a negative-feedback loop created by CsrA repression of CsrD production, which reduces the time for the system to achieve steady state. We also demonstrate that sequestration in the CsrA system results in signaling that is robust to growth rates because it does not rely on the slow dilution of molecules via cell division; therefore, signaling can occur even during growth arrest induced by starvation or antibiotic treatment.

A multistep epigenetic switch enables the stable inheritance of DNA methylation states.

In many prokaryotes and eukaryotes, DNA methylation at cis-regulatory sequences determines whether gene expression is on or off. Stable inheritance of these expression states is required in bacterial pathogenesis, cancer and developmental pathways. Here we delineate the factors that control the stability of these states by using the agn43 gene in Escherichia coli as a model system. Systematic disruption of this system shows that a functional switch requires the presence of several, rarely occupied, intermediate states that separate the 'on' and 'off' states. Cells that leave the on and off state enter different intermediate states, where there is a strong bias that drives cells back to their original state. The intermediate states therefore act as buffers that prevent back and forth switching. This mechanism of generating multiple states is an alternative to feedback regulation, and its general principle should be applicable to the analysis of other epigenetic switches and the design of synthetic circuits.

Direct comparison of small RNA and transcription factor signaling.

Small RNAs (sRNAs) and proteins acting as transcription factors (TFs) are the principal components of gene networks. These two classes of signaling molecules have distinct mechanisms of action; sRNAs control mRNA translation, whereas TFs control mRNA transcription. Here, we directly compare the properties of sRNA and TF signaling using mathematical models and synthetic gene circuits in Escherichia coli. We show the abilities of sRNAs to act on existing target mRNAs (as opposed to TFs, which alter the production of future target mRNAs) and, without needing to be first translated, have surprisingly little impact on the dynamics. Instead, the dynamics are primarily determined by the clearance rates, steady-state concentrations and response curves of the sRNAs and TFs; these factors determine the time delay before a target gene's expression can maximally respond to changes in sRNA and TF transcription. The findings are broadly applicable to the analysis of signaling in gene networks, and we demonstrate that they can be used to rationally reprogram the dynamics of synthetic circuits.

Regulatory consequences of gene translocation in bacteria.

Gene translocations play an important role in the plasticity and evolution of bacterial genomes. In this study, we investigated the impact on gene regulation of three genome organizational features that can be altered by translocations: (i) chromosome position; (ii) gene orientation; and (iii) the distance between a target gene and its transcription factor gene ('target-TF distance'). Specifically, we quantified the effect of these features on constitutive expression, transcription factor binding and/or gene expression noise using a synthetic network in Escherichia coli composed of a transcription factor (LacI repressor) and its target gene (yfp). Here we show that gene regulation is generally robust to changes in chromosome position, gene orientation and target-TF distance. The only demonstrable effect was that chromosome position alters constitutive expression, due to changes in gene copy number and local sequence effects, and that this determines maximum and minimum expression levels. The results were incorporated into a mathematical model which was used to quantitatively predict the responses of a simple gene network to gene translocations; the predictions were confirmed experimentally. In summary, gene translocation can modulate constitutive gene expression levels due to changes in chromosome position but it has minimal impact on other facets of gene regulation.

Disruption of small RNA signaling caused by competition for Hfq.

Small RNAs (sRNAs) regulate diverse pathways, including stress responses, virulence, and metabolism in Escherichia coli. At the center of this large sRNA regulatory network is the Hfq protein. Hfq mediates the binding of sRNAs to their target mRNAs; without Hfq, most sRNAs cannot efficiently regulate target mRNA expression. Here, we show in vivo that Hfq can be a limiting factor for sRNA activity and that it can be easily depleted, causing disruption of the sRNA network. Depletion of the available Hfq can occur when sRNAs and target mRNAs are transcribed at high levels without their partners, resulting in the sequestration of Hfq into sRNA-Hfq and target mRNA-Hfq complexes. This can be avoided by coordinating the transcription of sRNAs with their target mRNAs so that they are turned on and off together to maximize duplex formation and minimize Hfq sequestration. Therefore, the limited availability of Hfq results in a highly interdependent sRNA network, wherein the activity of each sRNA depends on the activity of the other sRNAs and target mRNAs in the network.

Fundamental relationship between operon organization and gene expression.

Half a century has passed since the discovery of operons (groups of genes that are transcribed together as a single mRNA). Despite the importance of operons in bacterial gene networks, the relationship between their organization and gene expression remains poorly understood. Here we show using synthetic operons in Escherichia coli that the expression of a given gene increases with the length of the operon and as its position moves farther from the end of the operon. These findings can be explained by a common mechanism; increasing the distance from the start of a gene to the end of the operon (termed the "transcription distance") provides more time for translation to occur during transcription, resulting in increased expression. We confirmed experimentally that the increased expression is indeed due to increased translation. Furthermore our analysis indicates the translation initiation rate for an mRNA is sixfold greater during transcription than after its release, which amplifies the impact of the transcription distance on gene expression. As a result of these mechanisms, gene expression increases by ∼40% for each 1,000 nucleotides of transcription distance. In summary, we demonstrate that a fundamental relationship exists between gene expression and the number, length, and order of the genes in an operon. This relationship has important implications for understanding the functional basis of genome organization and practical applications for synthetic biology.

Essential requirements for robust signaling in Hfq dependent small RNA networks.

Bacteria possess networks of small RNAs (sRNAs) that are important for modulating gene expression. At the center of many of these sRNA networks is the Hfq protein. Hfq's role is to quickly match cognate sRNAs and target mRNAs from among a large number of possible combinations and anneal them to form duplexes. Here we show using a kinetic model that Hfq can efficiently and robustly achieve this difficult task by minimizing the sequestration of sRNAs and target mRNAs in Hfq complexes. This sequestration can be reduced by two non-mutually exclusive kinetic mechanisms. The first mechanism involves heterotropic cooperativity (where sRNA and target mRNA binding to Hfq is influenced by other RNAs bound to Hfq); this cooperativity can selectively decrease singly-bound Hfq complexes and ternary complexes with non-cognate sRNA-target mRNA pairs while increasing cognate ternary complexes. The second mechanism relies on frequent RNA dissociation enabling the rapid cycling of sRNAs and target mRNAs among different Hfq complexes; this increases the probability the cognate ternary complex forms before the sRNAs and target mRNAs degrade. We further demonstrate that the performance of sRNAs in isolation is not predictive of their performance within a network. These findings highlight the importance of experimentally characterizing duplex formation in physiologically relevant contexts with multiple RNAs competing for Hfq. The model will provide a valuable framework for guiding and interpreting these experiments.

Multistability in the lactose utilization network of Escherichia coli.

Multistability, the capacity to achieve multiple internal states in response to a single set of external inputs, is the defining characteristic of a switch. Biological switches are essential for the determination of cell fate in multicellular organisms, the regulation of cell-cycle oscillations during mitosis and the maintenance of epigenetic traits in microbes. The multistability of several natural and synthetic systems has been attributed to positive feedback loops in their regulatory networks. However, feedback alone does not guarantee multistability. The phase diagram of a multistable system, a concise description of internal states as key parameters are varied, reveals the conditions required to produce a functional switch. Here we present the phase diagram of the bistable lactose utilization network of Escherichia coli. We use this phase diagram, coupled with a mathematical model of the network, to quantitatively investigate processes such as sugar uptake and transcriptional regulation in vivo. We then show how the hysteretic response of the wild-type system can be converted to an ultrasensitive graded response. The phase diagram thus serves as a sensitive probe of molecular interactions and as a powerful tool for rational network design.

EzColocalization: An ImageJ plugin for visualizing and measuring colocalization in cells and organisms.

Insight into the function and regulation of biological molecules can often be obtained by determining which cell structures and other molecules they localize with (i.e. colocalization). Here we describe an open source plugin for ImageJ called EzColocalization to visualize and measure colocalization in microscopy images. EzColocalization is designed to be easy to use and customize for researchers with minimal experience in quantitative microscopy and computer programming. Features of EzColocalization include: (i) tools to select individual cells and organisms from images; (ii) filters to select specific types of cells and organisms based on physical parameters and signal intensity; (iii) heat maps and scatterplots to visualize the localization patterns of reporters; (iv) multiple metrics to measure colocalization for two or three reporters; (v) metric matrices to systematically measure colocalization at multiple combinations of signal intensity thresholds; and (vi) data tables that provide detailed information on each cell in a sample. These features make EzColocalization well-suited for experiments with low reporter signal, complex patterns of localization, and heterogeneous populations of cells and organisms.

Systematic and general method for quantifying localization in microscopy images.

Quantifying the localization of molecules with respect to other molecules, cell structures and intracellular regions is essential to understanding their regulation and actions. However, measuring localization from microscopy images is often difficult with existing metrics. Here, we evaluate a metric for quantifying localization termed the threshold overlap score (TOS), and show it is simple to calculate, easy to interpret, able to be used to systematically characterize localization patterns, and generally applicable. TOS is calculated by: (i) measuring the overlap of pixels that are above the intensity thresholds for two signals; (ii) determining whether the overlap is more, less, or the same as expected by chance, i.e. colocalization, anti-colocalization, or non-colocalization; and (iii) rescaling to allow comparison at different thresholds. The above is repeated at multiple threshold combinations to generate a TOS matrix to systematically characterize the relationship between localization and signal intensities. TOS matrices were used to identify and distinguish localization patterns of different proteins in various simulations, cell types and organisms with greater specificity and sensitivity than common metrics. For all the above reasons, TOS is an excellent first line metric, particularly for cells with mixed localization patterns.

Evidence that luteinising hormone receptor polymorphisms may contribute to male undermasculinisation.

BACKGROUND: The luteinising hormone receptor (LHR) is necessary for the stimulation of androgen production and male genital development. It contains three protein polymorphisms: a leucine and glutamine insertion between codons 8 and 9 (LQ+) and two amino acid substitutions (N291S, N312S). OBJECTIVES: To determine whether these LHR polymorphisms are associated with male genital undermasculinisation or the androgen receptor polyglutamine repeat polymorphism (AR(Q)n), which contributes in some cases to the cause of genital undermasculinisation. METHODS: The LHR polymorphisms were assessed by PCR amplification of genomic DNA, followed by restriction enzyme analysis. The frequency of the LHR polymorphisms were compared between an undermasculinised male group (n=75) and a control group (n=55). RESULTS: LQ+ was not independently associated with the undermasculinised group (P=0.09), but it was associated with increased AR(Q)n within the undermasculinised group (P=0.02), particularly for AR(Q)n lengths >or=26 (P=0.002). In the undermasculinised group, homozygosity for N291 (872A/A) was more frequent (P=0.05), whereas homozygosity for N312 (935A/A) was less frequent (P=0.05). The combination of the presence of 872A/A and the absence of 935A/A showed a stronger association with the undermasculinised group than either polymorphism independently (P=0.006). The odds ratio of this genotype compared with any other, between the undermasculinised and control groups was 3.28 (95% confidence interval (CI) 1.33 to 8.08). CONCLUSION: LHR polymorphisms may contribute to genital undermasculinisation.

Modulating the frequency and bias of stochastic switching to control phenotypic variation.

Mechanisms that control cell-to-cell variation in gene expression ('phenotypic variation') can determine a population's growth rate, robustness, adaptability and capacity for complex behaviours. Here we describe a general strategy (termed FABMOS) for tuning the phenotypic variation and mean expression of cell populations by modulating the frequency and bias of stochastic transitions between 'OFF' and 'ON' expression states of a genetic switch. We validated the strategy experimentally using a synthetic fim switch in Escherichia coli. Modulating the frequency of switching can generate a bimodal (low frequency) or a unimodal (high frequency) population distribution with the same mean expression. Modulating the bias as well as the frequency of switching can generate a spectrum of bimodal and unimodal distributions with the same mean expression. This remarkable control over phenotypic variation, which cannot be easily achieved with standard gene regulatory mechanisms, has many potential applications for synthetic biology, engineered microbial ecosystems and experimental evolution.

Minimal effect of gene clustering on expression in Escherichia coli.

Genes that interact or function together are often clustered in bacterial genomes, and it has been proposed that this clustering may affect gene expression. In this study, we directly compared gene expression in nonclustered arrangements and in three common clustered arrangements (codirectional, divergent, and operon) using synthetic circuits in Escherichia coli. We found that gene clustering had minimal effects on gene expression. Specifically, gene clustering did not alter constitutive expression levels or stochastic fluctuations in expression ("expression noise"). Remarkably, the expression of two genes that share the same chromosome position with the same promoter (operon) or with separate promoters (codirectional and divergent arrangements) was not significantly more correlated than genes at different chromosome positions (nonclustered arrangements). The only observed effect of clustering was increased transcription factor binding in codirectional and divergent gene arrangements due to DNA looping, but this is not a specific feature of clustering. In summary, we demonstrate that gene clustering is not a general modulator of gene expression, and therefore any effects of clustering are likely to occur only with specific genes or under certain conditions.