Leaky resistance and the conditions for the existence of lytic bacteriophage.

In experimental cultures, when bacteria are mixed with lytic (virulent) bacteriophage, bacterial cells resistant to the phage commonly emerge and become the dominant population of bacteria. Following the ascent of resistant mutants, the densities of bacteria in these simple communities become limited by resources rather than the phage. Despite the evolution of resistant hosts, upon which the phage cannot replicate, the lytic phage population is most commonly maintained in an apparently stable state with the resistant bacteria. Several mechanisms have been put forward to account for this result. Here we report the results of population dynamic/evolution experiments with a virulent mutant of phage Lambda, λVIR, and Escherichia coli in serial transfer cultures. We show that, following the ascent of λVIR-resistant bacteria, λVIR is maintained in the majority of cases in maltose-limited minimal media and in all cases in nutrient-rich broth. Using mathematical models and experiments, we show that the dominant mechanism responsible for maintenance of λVIR in these resource-limited populations dominated by resistant E. coli is a high rate of either phenotypic or genetic transition from resistance to susceptibility-a hitherto undemonstrated mechanism we term "leaky resistance." We discuss the implications of leaky resistance to our understanding of the conditions for the maintenance of phage in populations of bacteria-their "existence conditions."

Epistatic Interactions in the Arabinose Cis-Regulatory Element.

Changes in gene expression are an important mode of evolution; however, the proximate mechanism of these changes is poorly understood. In particular, little is known about the effects of mutations within cis binding sites for transcription factors, or the nature of epistatic interactions between these mutations. Here, we tested the effects of single and double mutants in two cis binding sites involved in the transcriptional regulation of the Escherichia coli araBAD operon, a component of arabinose metabolism, using a synthetic system. This system decouples transcriptional control from any posttranslational effects on fitness, allowing a precise estimate of the effect of single and double mutations, and hence epistasis, on gene expression. We found that epistatic interactions between mutations in the araBAD cis-regulatory element are common, and that the predominant form of epistasis is negative. The magnitude of the interactions depended on whether the mutations are located in the same or in different operator sites. Importantly, these epistatic interactions were dependent on the presence of arabinose, a native inducer of the araBAD operon in vivo, with some interactions changing in sign (e.g., from negative to positive) in its presence. This study thus reveals that mutations in even relatively simple cis-regulatory elements interact in complex ways such that selection on the level of gene expression in one environment might perturb regulation in the other environment in an unpredictable and uncorrelated manner.

Effects of mutations in phage restriction sites during escape from restriction-modification.

Restriction-modification systems are widespread genetic elements that protect bacteria from bacteriophage infections by recognizing and cleaving heterologous DNA at short, well-defined sequences called restriction sites. Bioinformatic evidence shows that restriction sites are significantly underrepresented in bacteriophage genomes, presumably because bacteriophages with fewer restriction sites are more likely to escape cleavage by restriction-modification systems. However, how mutations in restriction sites affect the likelihood of bacteriophage escape is unknown. Using the bacteriophage λ and the restriction-modification system EcoRI, we show that while mutation effects at different restriction sites are unequal, they are independent. As a result, the probability of bacteriophage escape increases with each mutated restriction site. Our results experimentally support the role of restriction site avoidance as a response to selection imposed by restriction-modification systems and offer an insight into the events underlying the process of bacteriophage escape.

Interdependence of behavioural variability and response to small stimuli in bacteria.

The chemotaxis signalling network in Escherichia coli that controls the locomotion of bacteria is a classic model system for signal transduction. This pathway modulates the behaviour of flagellar motors to propel bacteria towards sources of chemical attractants. Although this system relaxes to a steady state in response to environmental changes, the signalling events within the chemotaxis network are noisy and cause large temporal variations of the motor behaviour even in the absence of stimulus. That the same signalling network governs both behavioural variability and cellular response raises the question of whether these two traits are independent. Here, we experimentally establish a fluctuation-response relationship in the chemotaxis system of living bacteria. Using this relationship, we demonstrate the possibility of inferring the cellular response from the behavioural variability measured before stimulus. In monitoring the pre- and post-stimulus switching behaviour of individual bacterial motors, we found that variability scales linearly with the response time for different functioning states of the cell. This study highlights that the fundamental relationship between fluctuation and response is not constrained to physical systems at thermodynamic equilibrium but is extensible to living cells. Such a relationship not only implies that behavioural variability and cellular response can be coupled traits, but it also provides a general framework within which we can examine how the selection of a network design shapes this interdependence.

Variation of the folding and dynamics of the Escherichia coli chromosome with growth conditions.

We examine whether the Escherichia coli chromosome is folded into a self-adherent nucleoprotein complex, or alternately is a confined but otherwise unconstrained self-avoiding polymer. We address this through in vivo visualization, using an inducible GFP fusion to the nucleoid-associated protein Fis to non-specifically decorate the entire chromosome. For a range of different growth conditions, the chromosome is a compact structure that does not fill the volume of the cell, and which moves from the new pole to the cell centre. During rapid growth, chromosome segregation occurs well before cell division, with daughter chromosomes coupled by a thin inter-daughter filament before complete segregation, whereas during slow growth chromosomes stay adjacent until cell division occurs. Image correlation analysis indicates that sub-nucleoid structure is stable on a 1 min timescale, comparable to the timescale for redistribution time measured for GFP-Fis after photobleaching. Optical deconvolution and writhe calculation analysis indicate that the nucleoid has a large-scale coiled organization rather than being an amorphous mass. Our observations are consistent with the chromosome having a self-adherent filament organization.

Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression.

In Gram negative bacteria, the multiple antibiotic resistance or mar operon, is known to control the expression of multi-drug efflux genes that protect bacteria from a wide range of drugs. As many different chemical compounds can induce this operon, identifying the parameters that govern the dynamics of its induction is crucial to better characterize the processes of tolerance and resistance. Most experiments have assumed that the properties of the mar transcriptional network can be inferred from population measurements. However, measurements from an asynchronous population of cells can mask underlying phenotypic variations of single cells. We monitored the activity of the mar promoter in single Escherichia coli cells in linear micro-colonies and established that the response to a steady level of inducer was most heterogeneous within individual colonies for an intermediate value of inducer. Specifically, sub-lineages defined by contiguous daughter-cells exhibited similar promoter activity, whereas activity was greatly variable between different sub-lineages. Specific sub-trees of uniform promoter activity persisted over several generations. Statistical analyses of the lineages suggest that the presence of these sub-trees is the signature of an inducible memory of the promoter state that is transmitted from mother to daughter cells. This single-cell study reveals that the degree of epigenetic inheritance changes as a function of inducer concentration, suggesting that phenotypic inheritance may be an inducible phenotype.

Adaptation dynamics between copy-number and point mutations.

Together, copy-number and point mutations form the basis for most evolutionary novelty, through the process of gene duplication and divergence. While a plethora of genomic data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic reporter system that can distinguish between copy-number and point mutations, we study their early and transient adaptive dynamics in real time in Escherichia coli. We find two qualitatively different routes of adaptation, depending on the level of functional improvement needed. In conditions of high gene expression demand, the two mutation types occur as a combination. However, under low gene expression demand, copy-number and point mutations are mutually exclusive; here, owing to their higher frequency, adaptation is dominated by copy-number mutations, in a process we term amplification hindrance. Ultimately, due to high reversal rates and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation, but also constrain sequence divergence over evolutionary time scales.

Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14.

A key attribute of persistent or recurring bacterial infections is the ability of the pathogen to evade the host's immune response. Many Enterobacteriaceae express type 1 pili, a pre-adapted virulence trait, to invade host epithelial cells and establish persistent infections. However, the molecular mechanisms and strategies by which bacteria actively circumvent the immune response of the host remain poorly understood. Here, we identified CD14, the major co-receptor for lipopolysaccharide detection, on mouse dendritic cells (DCs) as a binding partner of FimH, the protein located at the tip of the type 1 pilus of Escherichia coli. The FimH amino acids involved in CD14 binding are highly conserved across pathogenic and non-pathogenic strains. Binding of the pathogenic strain CFT073 to CD14 reduced DC migration by overactivation of integrins and blunted expression of co-stimulatory molecules by overactivating the NFAT (nuclear factor of activated T-cells) pathway, both rate-limiting factors of T cell activation. This response was binary at the single-cell level, but averaged in larger populations exposed to both piliated and non-piliated pathogens, presumably via the exchange of immunomodulatory cytokines. While defining an active molecular mechanism of immune evasion by pathogens, the interaction between FimH and CD14 represents a potential target to interfere with persistent and recurrent infections, such as urinary tract infections or Crohn's disease.

Predicting bacterial promoter function and evolution from random sequences.

Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10-20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought.

Noise underlies switching behavior of the bacterial flagellum.

We report the switching behavior of the full bacterial flagellum system that includes the filament and the motor in wild-type Escherichia coli cells. In sorting the motor behavior by the clockwise bias, we find that the distributions of the clockwise (CW) and counterclockwise (CCW) intervals are either exponential or nonexponential with long tails. At low bias, CW intervals are exponentially distributed and CCW intervals exhibit long tails. At intermediate CW bias (0.5) both CW and CCW intervals are mainly exponentially distributed. A simple model suggests that these two distinct switching behaviors are governed by the presence of signaling noise within the chemotaxis network. Low noise yields exponentially distributed intervals, whereas large noise yields nonexponential behavior with long tails. These drastically different motor statistics may play a role in optimizing bacterial behavior for a wide range of environmental conditions.

Fine-tuning of chemotactic response in E. coli determined by high-throughput capillary assay.

In E. coli, chemotactic behavior exhibits perfect adaptation that is robust to changes in the intracellular concentration of the chemotactic proteins, such as CheR and CheB. However, the robustness of the perfect adaptation does not explicitly imply a robust chemotactic response. Previous studies on the robustness of the chemotactic response relied on swarming assays, which can be confounded by processes besides chemotaxis, such as cellular growth and depletion of nutrients. Here, using a high-throughput capillary assay that eliminates the effects of growth, we experimentally studied how the chemotactic response depends on the relative concentration of the chemotactic proteins. We simultaneously measured both the chemotactic response of E. coli cells to L: -aspartate and the concentrations of YFP-CheR and CheB-CFP fusion proteins. We found that the chemotactic response is fine-tuned to a specific ratio of [CheR]/[CheB] with a maximum response comparable to the chemotactic response of wild-type behavior. In contrast to adaptation in chemotaxis, that is robust and exact, capillary assays revealed that the chemotactic response in swimming bacteria is fined-tuned to wild-type level of the [CheR]/[CheB] ratio.

Local genetic context shapes the function of a gene regulatory network.

Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks (GRNs) remains a major challenge. Here, we use a well-defined synthetic GRN to study in Escherichia coli how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one GRN with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Transcriptional read-through is the main molecular mechanism that places one transcriptional unit (TU) within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual TUs, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of GRNs.

Minimally invasive determination of mRNA concentration in single living bacteria.

Fluorescence correlation spectroscopy (FCS) has permitted the characterization of high concentrations of noncoding RNAs in a single living bacterium. Here, we extend the use of FCS to low concentrations of coding RNAs in single living cells. We genetically fuse a red fluorescent protein (RFP) gene and two binding sites for an RNA-binding protein, whose translated product is the RFP protein alone. Using this construct, we determine in single cells both the absolute [mRNA] concentration and the associated [RFP] expressed from an inducible plasmid. We find that the FCS method allows us to reliably monitor in real-time [mRNA] down to approximately 40 nM (i.e. approximately two transcripts per volume of detection). To validate these measurements, we show that [mRNA] is proportional to the associated expression of the RFP protein. This FCS-based technique establishes a framework for minimally invasive measurements of mRNA concentration in individual living bacteria.

Modeling network dynamics: the lac operon, a case study.

We use the lac operon in Escherichia coli as a prototype system to illustrate the current state, applicability, and limitations of modeling the dynamics of cellular networks. We integrate three different levels of description (molecular, cellular, and that of cell population) into a single model, which seems to capture many experimental aspects of the system.

Lack of cations in flow cytometry buffers affect fluorescence signals by reducing membrane stability and viability of Escherichia coli strains.

Buffers are essential for diluting bacterial cultures for flow cytometry analysis in order to study bacterial physiology and gene expression parameters based on fluorescence signals. Using a variety of constitutively expressed fluorescent proteins in Escherichia coli K-12 strain MG1655, we found strong artifactual changes in fluorescence levels after dilution into the commonly used flow cytometry buffer phosphate-buffered saline (PBS) and two other buffer solutions, Tris-HCl and M9 salts. These changes appeared very rapidly after dilution, and were linked to increased membrane permeability and loss in cell viability. We observed buffer-related effects in several different E. coli strains, K-12, C and W, but not E. coli B, which can be partially explained by differences in lipopolysaccharide (LPS) and outer membrane composition. Supplementing the buffers with divalent cations responsible for outer membrane stability, Mg2+ and Ca2+, preserved fluorescence signals, membrane integrity and viability of E. coli. Thus, stabilizing the bacterial outer membrane is essential for precise and unbiased measurements of fluorescence parameters using flow cytometry.

Statistical mechanics for metabolic networks during steady state growth.

Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.

Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity.

Temperate bacteriophages integrate in bacterial genomes as prophages and represent an important source of genetic variation for bacterial evolution, frequently transmitting fitness-augmenting genes such as toxins responsible for virulence of major pathogens. However, only a fraction of bacteriophage infections are lysogenic and lead to prophage acquisition, whereas the majority are lytic and kill the infected bacteria. Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity to bacteriophages are expected to act as a double-edged sword and increase the odds of survival at the cost of depriving bacteria of potentially beneficial prophages. We show that although restriction-modification systems as mechanisms of innate immunity prevent both lytic and lysogenic infections indiscriminately in individual bacteria, they increase the number of prophage-acquiring individuals at the population level. We find that this counterintuitive result is a consequence of phage-host population dynamics, in which restriction-modification systems delay infection onset until bacteria reach densities at which the probability of lysogeny increases. These results underscore the importance of population-level dynamics as a key factor modulating costs and benefits of immunity to temperate bacteriophages.

Evolutionary potential of transcription factors for gene regulatory rewiring.

Gene regulatory networks evolve through rewiring of individual components-that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor-DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor-DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.

Complex chromosomal neighborhood effects determine the adaptive potential of a gene under selection.

How the organization of genes on a chromosome shapes adaptation is essential for understanding evolutionary paths. Here, we investigate how adaptation to rapidly increasing levels of antibiotic depends on the chromosomal neighborhood of a drug-resistance gene inserted at different positions of the Escherichia coli chromosome. Using a dual-fluorescence reporter that allows us to distinguish gene amplifications from other up-mutations, we track in real-time adaptive changes in expression of the drug-resistance gene. We find that the relative contribution of several mutation types differs systematically between loci due to properties of neighboring genes: essentiality, expression, orientation, termination, and presence of duplicates. These properties determine rate and fitness effects of gene amplification, deletions, and mutations compromising transcriptional termination. Thus, the adaptive potential of a gene under selection is a system-property with a complex genetic basis that is specific for each chromosomal locus, and it can be inferred from detailed functional and genomic data.

Shaping bacterial population behavior through computer-interfaced control of individual cells.

Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.