Evolution of Escherichia coli in different carbon environments for 2,000 generations.

Cellular energetics is thought to have played a key role in dictating all major evolutionary transitions in the history of life on Earth. However, how exactly cellular energetics and metabolism come together to shape evolutionary paths is not well understood. In particular, when an organism is evolved in different energy environments, what are the phenomenological differences in the chosen evolutionary trajectories, is a question that is not well understood. In this context, starting from an Escherichia coli K-12 strain, we evolve the bacterium in five different carbon environments-glucose, arabinose, xylose, rhamnose and a mixture of these four sugars (in a predefined ratio) for approximately 2,000 generations. At the end of the adaptation period, we quantify and compare the growth dynamics of the strains in a variety of environments. The evolved strains show no specialized adaptation towards growth in the carbon medium in which they were evolved. Rather, in all environments, the evolved strains exhibited a reduced lag phase and an increased growth rate. Sequencing results reveal that these dynamical properties are not introduced via mutations in the precise loci associated with utilization of the sugar in which the bacterium evolved. These phenotypic changes are rather likely introduced via mutations elsewhere on the genome. Data from our experiments indicate that evolution in a defined environment does not alter hierarchy in mixed-sugar utilization in bacteria.

Phenomenological models as effective tools to discover cellular design principles.

Microbes have proved useful to us in many different ways. To utilize microbes, we have mostly focused on maximizing growth, to improve yield of chemicals derived from the microbes. However, to truly tap into their potential, we should also aim to understand microbial physiology. We present a historical perspective of the developments in the field of Microbial Biotechnology, focusing on how the growth-modelling approaches have changed. Starting from simple empirical growth models, we have evolved towards mechanistic and phenomenological models which use molecular and physiological details to drastically improve prediction power of these models. Lastly, we explore the as of yet unsolved questions in microbial physiology, and discuss how the ability to monitor microbial growth at single cell resolution using the lab-on-a-chip technologies is uncovering previously unobservable causal principles underlying microbial growth.

Control of MarRAB Operon in Escherichia coli via Autoactivation and Autorepression.

Choice of network topology for gene regulation has been a question of interest for a long time. How do simple and more complex topologies arise? In this work, we analyze the topology of the marRAB operon in Escherichia coli, which is associated with control of expression of genes associated with conferring resistance to low-level antibiotics to the bacterium. Among the 2102 promoters in E. coli, the marRAB promoter is the only one that encodes for an autoactivator and an autorepressor. What advantages does this topology confer to the bacterium? In this work, we demonstrate that, compared to control by a single regulator, the marRAB regulatory arrangement has the least control cost associated with modulating gene expression in response to environmental stimuli. In addition, the presence of dual regulators allows the regulon to exhibit a diverse range of dynamics, a feature that is not observed in genes controlled by a single regulator.

Increased privatization of a public resource leads to spread of cooperation in a microbial population.

The phenomenon of cooperation is prevalent at all levels of life. In one such manifestation of cooperation in microbial communities, some cells produce costly extracellular resources that are freely available to others. These resources are referred to as public goods. Saccharomyces cerevisiae secretes invertase (public good) in the periplasm to hydrolyze sucrose into glucose and fructose, which are then imported by the cells. After hydrolysis of sucrose, a cooperator retains only 1% of the monosaccharides, while 99% of the monosaccharides diffuse into the environment and can be utilized by any cell. The non-producers of invertase (cheaters) exploit the invertase-producing cells (cooperators) by utilizing the monosaccharides and not paying the metabolic cost of producing the invertase. In this work, we investigate the evolutionary dynamics of this cheater-cooperator system. In a co-culture, if cheaters are selected for their higher fitness, the population will collapse. On the other hand, for cooperators to survive in the population, a strategy to increase fitness would likely be required. To understand the adaptation of cooperators in sucrose, we performed a coevolution experiment in sucrose. Our results show that cooperators increase in fitness as the experiment progresses. This phenomenon was not observed in environments which involved a non-public good system. Genome sequencing reveals duplication of several HXT transporters in the evolved cooperators. Based on these results, we hypothesize that increased privatization of the monosaccharides is the most likely explanation of spread of cooperators in the population.IMPORTANCEHow is cooperation, as a trait, maintained in a population? In order to answer this question, we perform a coevolution experiment between two strains of yeast-one which produces a public good to release glucose and fructose in the media, thus generating a public resource, and the other which does not produce public resource and merely benefits from the presence of the cooperator strain. What is the outcome of this coevolution experiment? We demonstrate that after ~200 generations of coevolution, cooperators increase in frequency in the co-culture. Remarkably, in all parallel lines of our experiment, this is obtained via duplication of regions which likely allow greater privatization of glucose and fructose. Thus, increased privatization, which is intuitively thought to be a strategy against cooperation, enables spread of cooperation.

Ecological disruptive selection acting on quantitative loci can drive sympatric speciation.

The process of speciation generates biodiversity. According to the null model of speciation, barriers between populations arise in allopatry, where, prior to biology, geography imposes barriers to gene flow. On the other hand, sympatric speciation requires that the process of speciation happen in the absence of a geographical barrier, where the members of the population have no spatial, temporal barriers. Several attempts have been made to theoretically identify the conditions in which speciation can occur in sympatry. However, these efforts suffer from several limitations. We propose a model for sympatric speciation based on adaptation for resource utilization. We use a genetics-based model to investigate the relative roles of prezygotic and postzygotic barriers, from the context of ecological disruptive selection, sexual selection, and genetic architecture, in causing and maintaining sympatric speciation. Our results show that sexual selection that acts on secondary sexual traits does not play any role in the process of speciation in sympatry and that assortative mating based on an ecologically relevant trait forces the population to show an adaptive response. We also demonstrate that understanding the genetic architecture of the trait under ecological selection is very important and that it is not required for the strength of ecological disruptive selection to be very high in order for speciation to occur in sympatry. Our results provide an insight into the kind of scenarios in which sympatric speciation can be demonstrated in the lab.

Convergent genetic adaptation of Escherichia coli in minimal media leads to pleiotropic divergence.

Adaptation in an environment can either be beneficial, neutral or disadvantageous in another. To test the genetic basis of pleiotropic behaviour, we evolved six lines of E. coli independently in environments where glucose and galactose were the sole carbon sources, for 300 generations. All six lines in each environment exhibit convergent adaptation in the environment in which they were evolved. However, pleiotropic behaviour was observed in several environmental contexts, including other carbon environments. Genome sequencing reveals that mutations in global regulators rpoB and rpoC cause this pleiotropy. We report three new alleles of the rpoB gene, and one new allele of the rpoC gene. The novel rpoB alleles confer resistance to Rifampicin, and alter motility. Our results show how single nucleotide changes in the process of adaptation in minimal media can lead to wide-scale pleiotropy, resulting in changes in traits that are not under direct selection.

Exploring the Influence of pH on the Dynamics of Acetone-Butanol-Ethanol Fermentation.

Clostridium acetobutylicum is an anaerobic bacterium that is extensively studied for its ability to produce butanol. Over the past two decades, various genetic and metabolic engineering approaches have been used to investigate the physiology and regulation system of the biphasic metabolic pathway in this organism. However, there has been a relatively limited amount of research focused on the fermentation dynamics of C. acetobutylicum. In this study, we developed a pH-based phenomenological model to predict the fermentative production of butanol from glucose using C. acetobutylicum in a batch system. The model describes the relationship between the dynamics of growth and the production of desired metabolites and the extracellular pH of the media. Our model was found to be successful in predicting the fermentation dynamics of C. acetobutylicum, and the simulations were validated using experimental fermentation data. Furthermore, the proposed model has the potential to be extended to represent the dynamics of butanol production in other fermentation systems, such as fed-batch or continuous fermentation using single and multi-sugars.

Rapid evolution of pre-zygotic reproductive barriers in allopatric populations.

IMPORTANCE: A population diversifies into two or more species-such a process is known as speciation. In sexually reproducing microorganisms, which barriers arise first-pre-mating or post-mating? In this work, we quantify the relative strengths of these barriers and demonstrate that pre-mating barriers arise first in allopatrically evolving populations of yeast, Saccharomyces cerevisiae. These defects arise because of the altered kinetics of mating of the participating groups. Thus, our work provides an understanding of how adaptive changes can lead to diversification among microbial populations.

Continuous control of flagellar gene expression by the σ28-FlgM regulatory circuit in Salmonella enterica.

The flagellar genes in Salmonella enterica are expressed in a temporal hierarchy that mirrors the assembly process itself. The σ(28)-FlgM regulatory circuit plays a key role in controlling this temporal hierarchy. This circuit ensures that the class 3 genes are expressed only when the hook-basal body (HBB), a key intermediate in flagellar assembly, is complete. In this work, we investigated the role of the σ(28)-FlgM regulatory circuit in controlling the timing and magnitude of class 3 gene expression using a combination of mathematical modelling and experimental analysis. Analysis of the model predicted that this circuit continuously controls class 3 gene expression in response to HBB abundance. We experimentally validated these predictions by eliminating different components of the σ(28)-FlgM regulatory system and also by rewiring the transcriptional hierarchy. Based on these results, we conclude that the σ(28)-FlgM regulatory circuit continuously senses the HBB assembly process and regulates class 3 gene expression and possibly flagellar numbers in response.

Correction: The role of coupled positive feedback in the expression of the SPI1 type three secretion system in Salmonella.

Salmonella enterica serovar Typhimurium is a common food-borne pathogen that induces inflammatory diarrhea and invades intestinal epithelial cells using a type three secretion system (T3SS) encoded within Salmonella pathogenicity island 1 (SPI1). The genes encoding the SPI1 T3SS are tightly regulated by a network of interacting transcriptional regulators involving three coupled positive feedback loops. While the core architecture of the SPI1 gene circuit has been determined, the relative roles of these interacting regulators and associated feedback loops are still unknown. To determine the function of this circuit, we measured gene expression dynamics at both population and single-cell resolution in a number of SPI1 regulatory mutants. Using these data, we constructed a mathematical model of the SPI1 gene circuit. Analysis of the model predicted that the circuit serves two functions. The first is to place a threshold on SPI1 activation, ensuring that the genes encoding the T3SS are expressed only in response to the appropriate combination of environmental and cellular cues. The second is to amplify SPI1 gene expression. To experimentally test these predictions, we rewired the SPI1 genetic circuit by changing its regulatory architecture. This enabled us to directly test our predictions regarding the function of the circuit by varying the strength and dynamics of the activating signal. Collectively, our experimental and computational results enable us to deconstruct this complex circuit and determine the role of its individual components in regulating SPI1 gene expression dynamics.

The role of coupled positive feedback in the expression of the SPI1 type three secretion system in Salmonella.

Salmonella enterica serovar Typhimurium is a common food-borne pathogen that induces inflammatory diarrhea and invades intestinal epithelial cells using a type three secretion system (T3SS) encoded within Salmonella pathogenicity island 1 (SPI1). The genes encoding the SPI1 T3SS are tightly regulated by a network of interacting transcriptional regulators involving three coupled positive feedback loops. While the core architecture of the SPI1 gene circuit has been determined, the relative roles of these interacting regulators and associated feedback loops are still unknown. To determine the function of this circuit, we measured gene expression dynamics at both population and single-cell resolution in a number of SPI1 regulatory mutants. Using these data, we constructed a mathematical model of the SPI1 gene circuit. Analysis of the model predicted that the circuit serves two functions. The first is to place a threshold on SPI1 activation, ensuring that the genes encoding the T3SS are expressed only in response to the appropriate combination of environmental and cellular cues. The second is to amplify SPI1 gene expression. To experimentally test these predictions, we rewired the SPI1 genetic circuit by changing its regulatory architecture. This enabled us to directly test our predictions regarding the function of the circuit by varying the strength and dynamics of the activating signal. Collectively, our experimental and computational results enable us to deconstruct this complex circuit and determine the role of its individual components in regulating SPI1 gene expression dynamics.

GAL Regulon in the Yeast S. cerevisiae is Highly Evolvable via Acquisition in the Coding Regions of the Regulatory Elements of the Network.

GAL network in the yeast S. cerevisiae is one of the most well-characterized regulatory network. Expression of GAL genes is contingent on exposure to galactose, and an appropriate combination of the alleles of the regulatory genes GAL3, GAL1, GAL80, and GAL4. The presence of multiple regulators in the GAL network makes it unique, as compared to the many sugar utilization networks studied in bacteria. For example, utilization of lactose is controlled by a single regulator LacI, in E. coli's lac operon. Moreover, recent work has demonstrated that multiple alleles of these regulatory proteins are present in yeast isolated from ecological niches. In this work, we develop a mathematical model, and demonstrate via deterministic and stochastic runs of the model, that behavior/gene expression patterns of the cells (at a population level, and at a single-cell resolution) can be modulated by altering the binding affinities between the regulatory proteins. This adaptability is likely the key to explaining the multiple GAL regulatory alleles discovered in ecological isolates in recent years.

Determination of the Mating Efficiency of Haploids in Saccharomyces cerevisiae.

Saccharomyces cerevisiae is a widely used model organism in genetics, evolution, and molecular biology. In recent years, it has also become a popular model organism to study problems related to speciation. The life cycle of yeast involves both asexual and sexual reproductive phases. The ease of performing evolution experiments and the short generation time of the organism allow for the study of the evolution of reproductive barriers. The efficiency with which the two mating types (a and α) mate to form the a/α diploid is referred to as the mating efficiency. Any decrease in the mating efficiency between haploids indicates a pre-zygotic barrier. Thus, to quantify the extent of reproductive isolation between two haploids, a robust method to quantify the mating efficiency is required. To this end, a simple and highly reproducible protocol is presented here. The protocol involves four main steps, which include patching the haploids on a YPD plate, mixing the haploids in equal numbers, diluting and plating for single colonies, and finally, calculating the efficiency based on the number of colonies on a drop-out plate. Auxotrophic markers are employed to clearly make the distinction between haploids and diploids.

Selection in a growing colony biases results of mutation accumulation experiments.

Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments can be performed with different effective population sizes. In MA experiments with bacteria, a single founder is grown to a size of a colony (~ 108). It is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth. In this work, we simulate colony growth via a mathematical model, and use our model to mimic an MA experiment. We demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over-represented by a factor of almost two, and that the distribution of fitness effects of beneficial and deleterious mutations are inaccurately captured in an MA experiment. Given this, the estimate of mutation rates from MA experiments is non-trivial. We then perform an MA experiment with 160 lines of E. coli, and show that due to the effect of selection in a growing colony, the size and sector of a colony from which the experiment is propagated impacts the results. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

Public good-driven release of heterogeneous resources leads to genotypic diversification of an isogenic yeast population.

Understanding the basis of biological diversity remains a central problem in evolutionary biology. Using microbial systems, adaptive diversification has been studied in (a) spatially heterogeneous environments, (b) temporally segregated resources, and (c) resource specialization in a homogeneous environment. However, it is not well understood how adaptive diversification can take place in a homogeneous environment containing a single resource. Starting from an isogenic population of yeast Saccharomyces cerevisiae, we report rapid adaptive diversification, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good enzyme α-galactosidase, which hydrolyzes melibiose into glucose and galactose. The diversification is driven by mutations at a single locus, in the GAL3 gene in the S. cerevisiae GAL/MEL regulon. We show that metabolic co-operation involving public resources could be an important mode of generating biological diversity. Our study demonstrates sympatric diversification of yeast starting from an isogenic population and provides detailed mechanistic insights into the factors and conditions responsible for generating and maintaining the population diversity.

The interaction dynamics of a negative feedback loop regulates flagellar number in Salmonella enterica serovar Typhimurium.

Each Salmonella enterica serovar Typhimurium cell produces a discrete number of complete flagella. Flagellar assembly responds to changes in growth rates through FlhD(4) C(2) activity. FlhD(4) C(2) activity is negatively regulated by the type 3 secretion chaperone FliT. FliT is known to interact with the flagellar filament cap protein FliD as well as components of the flagellar type 3 secretion apparatus. FliD is proposed to act as an anti-regulator, in a manner similar to FlgM inhibition of σ(28) activity. We have found that efficient growth-dependent regulation of FlhD(4) C(2) requires FliT regulation. In turn, FliD regulation of FliT modulates the response. We also show that, unlike other flagellar-specific regulatory circuits, deletion of fliT or fliD did not lead to an all-or-nothing response in FlhD(4) C(2) activity. To investigate why, we characterized the biochemical interactions in the FliT : FliD : FlhD(4) C(2) circuit. When FlhD(4) C(2) was not bound to DNA, FliT disrupted the FlhD(4) C(2) complex. Interestingly, when FlhD(4) C(2) was bound to DNA it was insensitive to FliT regulation. This suggests that the FliT circuit regulates FlhD(4) C(2) activity by preventing the formation of the FlhD(4) C(2) :DNA complex. Our data would suggest that this level of endogenous regulation of FlhD(4) C(2) activity allows the flagellar system to efficiently respond to external signals.

Cell Growth Model with Stochastic Gene Expression Helps Understand the Growth Advantage of Metabolic Exchange and Auxotrophy.

During cooperative growth, microbes often experience higher fitness by sharing resources via metabolite exchange. How competitive species evolve to cooperate is, however, not known. Moreover, existing models (based on optimization of steady-state resources or fluxes) are often unable to explain the growth advantage for the cooperating species, even for simple reciprocally cross-feeding auxotrophic pairs. We present here an abstract model of cell growth that considers the stochastic burst-like gene expression of biosynthetic pathways of limiting biomass precursor metabolites and directly connect the amount of metabolite produced to cell growth and division, using a "metabolic sizer/adder" rule. Our model recapitulates Monod's law and yields the experimentally observed right-skewed long-tailed distribution of cell doubling times. The model further predicts the growth effect of secretion and uptake of metabolites by linking it to changes in the internal metabolite levels. The model also explains why auxotrophs may grow faster when supplied with the metabolite they cannot produce and why two reciprocally cross-feeding auxotrophs can grow faster than prototrophs. Overall, our framework allows us to predict the growth effect of metabolic interactions in independent microbes and microbial communities, setting up the stage to study the evolution of these interactions. IMPORTANCE Cooperative behaviors are highly prevalent in the wild, but their evolution is not understood. Metabolic flux models can demonstrate the viability of metabolic exchange as cooperative interactions, but steady-state growth models cannot explain why cooperators grow faster. We present a stochastic model that connects growth to the cell's internal metabolite levels and quantifies the growth effect of metabolite exchange and auxotrophy. We show that a reduction in gene expression noise can explain why cells that import metabolites or become auxotrophs can grow faster and why reciprocal cross-feeding of metabolites between complementary auxotrophs allows them to grow faster. Furthermore, our framework can simulate the growth of interacting cells, which will enable us to understand the possible trajectories of the evolution of cooperation in silico.

Experimental Evolution of Anticipatory Regulation in Escherichia coli.

Environmental cues in an ecological niche are often temporal in nature. For instance, in temperate climates, temperature is higher in daytime compared to during night. In response to these temporal cues, bacteria have been known to exhibit anticipatory regulation, whereby triggering response to a yet to appear cue. Such an anticipatory response in known to enhance Darwinian fitness, and hence, is likely an important feature of regulatory networks in microorganisms. However, the conditions under which an anticipatory response evolves as an adaptive response are not known. In this work, we develop a quantitative model to study response of a population to two temporal environmental cues, and predict variables which are likely important for evolution of anticipatory regulatory response. We follow this with experimental evolution of Escherichia coli in alternating environments of rhamnose and paraquat for ∼850 generations. We demonstrate that growth in this cyclical environment leads to evolution of anticipatory regulation. As a result, pre-exposure to rhamnose leads to a greater fitness in paraquat environment. Genome sequencing reveals that this anticipatory regulation is encoded via mutations in global regulators. Overall, our study contributes to understanding of how environment shapes the topology of regulatory networks in an organism.

SprB is the molecular link between Salmonella pathogenicity island 1 (SPI1) and SPI4.

Salmonella pathogenicity island 1 (SPI1) and SPI4 have previously been shown to be jointly regulated. We report that SPI1 and SPI4 gene expression is linked through a transcriptional activator, SprB, encoded within SPI1 and regulated by HilA. SprB directly activates SPI4 gene expression and weakly represses SPI1 gene expression through HilD.

Role of cross talk in regulating the dynamic expression of the flagellar Salmonella pathogenicity island 1 and type 1 fimbrial genes.

Salmonella enterica, a common food-borne pathogen, differentially regulates the expression of multiple genes during the infection cycle. These genes encode systems related to motility, adhesion, invasion, and intestinal persistence. Key among them is a type three secretion system (T3SS) encoded within Salmonella pathogenicity island 1 (SPI1). In addition to the SPI1 T3SS, other systems, including flagella and type 1 fimbriae, have been implicated in Salmonella pathogenesis. In this study, we investigated the dynamic expression of the flagellar, SPI1, and type 1 fimbrial genes. We demonstrate that these genes are expressed in a temporal hierarchy, beginning with the flagellar genes, followed by the SPI1 genes, and ending with the type 1 fimbrial genes. This hierarchy could mirror the roles of these three systems during the infection cycle. As multiple studies have shown that extensive regulatory cross talk exists between these three systems, we also tested how removing different regulatory links between them affects gene expression dynamics. These results indicate that cross talk is critical for regulating gene expression during transitional phases in the gene expression hierarchy. In addition, we identified a novel regulatory link between flagellar and type 1 fimbrial gene expression dynamics, where we found that the flagellar regulator, FliZ, represses type 1 fimbrial gene expression through the posttranscriptional regulation of FimZ. The significance of these results is that they provide the first systematic study of the effect of regulatory cross talk on the expression dynamics of flagellar, SPI1, and type 1 fimbrial genes.