Functional and metabolic effects of adaptive glycerol kinase (GLPK) mutants in Escherichia coli

Evolution and stability of complex microbial communities driven by trade-offs

Microbial communities are ubiquitous in nature and play an important role in ecology and human health. Cross-feeding is thought to be core to microbial communities, though it remains unclear precisely why it emerges. Why have multi-species microbial communities evolved in many contexts and what protects microbial consortia from invasion? Here, we review recent insights into the emergence and stability of coexistence in microbial communities. A particular focus is the long-term evolutionary stability of coexistence, as observed for microbial communities that spontaneously evolved in the E. coli long-term evolution experiment (LTEE). We analyze these findings in the context of recent work on trade-offs between competing microbial objectives, which can constitute a mechanistic basis for the emergence of coexistence. Coexisting communities, rather than monocultures of the 'fittest' single strain, can form stable endpoints of evolutionary trajectories. Hence, the emergence of coexistence might be an obligatory outcome in the evolution of microbial communities. This implies that rather than embodying fragile metastable configurations, some microbial communities can constitute formidable ecosystems that are difficult to disrupt.

Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli

Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.

Plasticity of growth laws tunes resource allocation strategies in bacteria

Bacteria like E. coli grow at vastly different rates on different substrates, however, the precise reason for this variability is poorly understood. Different growth rates have been attributed to 'nutrient quality', a key parameter in bacterial growth laws. However, it remains unclear to what extent nutrient quality is rooted in fundamental biochemical constraints like the energy content of nutrients, the protein cost required for their uptake and catabolism, or the capacity of the plasma membrane for nutrient transporters. Here, we show that while nutrient quality is indeed reflected in protein investment in substrate-specific transporters and enzymes, this is not a fundamental limitation on growth rate, at least for certain 'poor' substrates. We show that it is possible to turn mannose, one of the 'poorest' substrates of E. coli, into one of the 'best' substrates by reengineering chromosomal promoters of the mannose transporter and metabolic enzymes required for mannose degradation. This result falls in line with previous observations of more subtle growth rate improvement for many other carbon sources. However, we show that this faster growth rate comes at the cost of diverse cellular capabilities, reflected in longer lag phases, worse starvation survival and lower motility. We show that addition of cAMP to the medium can rescue these phenotypes but imposes a corresponding growth cost. Based on these data, we propose that nutrient quality is largely a self-determined, plastic property that can be modulated by the fraction of proteomic resources devoted to a specific substrate in the much larger proteome sector of catabolically activated genes. Rather than a fundamental biochemical limitation, nutrient quality reflects resource allocation decisions that are shaped by evolution in specific ecological niches and can be quickly adapted if necessary.

A Cell-Free Multi-enzyme Cascade Reaction for the Synthesis of CDP-Glycerol

CDP-glycerol is a nucleotide-diphosphate-activated version of glycerol. In nature, it is required for the biosynthesis of teichoic acid in Gram-positive bacteria, which is an appealing target epitope for the development of new vaccines. Here, a cell-free multi-enzyme cascade was developed to synthetize nucleotide-activated glycerol from the inexpensive and readily available substrates cytidine and glycerol. The cascade comprises five recombinant enzymes expressed in Escherichia coli that were purified by immobilized metal affinity chromatography. As part of the cascade, ATP is regenerated in situ from polyphosphate to reduce synthesis costs. The enzymatic cascade was characterized at the laboratory scale, and the products were analyzed by high-performance anion-exchange chromatography (HPAEC)-UV and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). After the successful synthesis had been confirmed, a design-of-experiments approach was used to screen for optimal operation conditions (temperature, pH value and MgCl2 concentration). Overall, a substrate conversion of 89 % was achieved with respect to the substrate cytidine.

Trade-offs between the instantaneous growth rate and long-term fitness: Consequences for microbial physiology and predictive computational models

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade-offs between cellular objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long-term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework.

Plasticity of growth laws tunes resource allocation strategies in bacteria

Bacteria like E. coli grow at vastly different rates on different substrates, however, the precise reason for this variability is poorly understood. Different growth rates have been attributed to 'nutrient quality', a key parameter in bacterial growth laws. However, it remains unclear to what extent nutrient quality is rooted in fundamental biochemical constraints like the energy content of nutrients, the protein cost required for their uptake and catabolism, or the capacity of the plasma membrane for nutrient transporters. Here, we show that while nutrient quality is indeed reflected in protein investment in substrate-specific transporters and enzymes, this is not a fundamental limitation on growth rate. We show that it is possible to turn mannose, one of the 'poorest' substrates of E. coli, into one of the 'best' substrates by reengineering chromosomal promoters of the mannose transporter and metabolic enzymes required for mannose degradation. However, we show that this faster growth rate comes at the cost of diverse cellular capabilities, reflected in longer lag phases, worse starvation survival and lower motility. We show that addition of cAMP to the medium can rescue these phenotypes but imposes a corresponding growth cost. Based on these data, we propose that nutrient quality is largely a self-determined, plastic property that can be modulated by the fraction of proteomic resources devoted to a specific substrate in the much larger proteome sector of catabolically activated genes. Rather than a fundamental biochemical limitation, nutrient quality reflects resource allocation decisions that are shaped by evolution in specific ecological niches and can be quickly adapted if necessary.

Evolution and function analysis of glycerol kinase GlpK in Pseudomonasaeruginosa

Pseudomonas aeruginosa is a Gram-negative bacterium capable of widespread niches, which is also one of the main bacteria that cause patient infection. The metabolic diversity of Pseudomonas aeruginosa is an essential factor in adapting to a variety of environments. Based on the previous studies, adaptive genetic variation in the glycerol kinase GlpK, the glycerol 3-phosphotransferase, contributes to the fitness of bacteria in human bodies, such as Mycobacterium tuberculosis and Escherichia coli. Thus, this study aimed to explore the molecular evolution and function of glpK in P. aeruginosa. Using extensive population genomic data, we have identified the prevalence of two glpK copies in P. aeruginosa that clustered into distinct branches, which were later known as Clade 1 and 2. The evolution analysis revealed that glpK in Clade 1 derived from an ancestral P. aeruginosa species and the other from an ancient horizontal gene transfer event. In addition, we confirmed that the GlpK in Clade 2 still retained glycerol kinase activity but was much weaker than that of GlpK in Clade 1. We demonstrated the importance of the critical amino acid Q70 in GlpK glycerol kinase activity by point mutation. Furthermore, Co-expression network analysis implied that the two glpK copies of P. aeruginosa regulate separate networks and may be a strategy to improve fitness in P. aeruginosa.

Minireview: Engineering evolution to reconfigure phenotypic traits in microbes for biotechnological applications

Adaptive laboratory evolution (ALE) has long been used as the tool of choice for microbial engineering applications, ranging from the production of commodity chemicals to the innovation of complex phenotypes. With the advent of systems and synthetic biology, the ALE experimental design has become increasingly sophisticated. For instance, implementation of in silico metabolic model reconstruction and advanced synthetic biology tools have facilitated the effective coupling of desired traits to adaptive phenotypes. Furthermore, various multi-omic tools now enable in-depth analysis of cellular states, providing a comprehensive understanding of the biology of even the most genomically perturbed systems. Emerging machine learning approaches would assist in streamlining the interpretation of massive and multiplexed datasets and promoting our understanding of complexity in biology. This review covers some of the representative case studies among the 700 independent ALE studies reported to date, outlining key ideas, principles, and important mechanisms underlying ALE designs in bioproduction and synthetic cell engineering, with evidence from literatures to aid comprehension.

ATP Recycling Fuels Sustainable Glycerol 3-Phosphate Formation in Synthetic Cells Fed by Dynamic Dialysis

The bottom-up construction of an autonomously growing, self-reproducing cell represents a great challenge for synthetic biology. Synthetic cellular systems are envisioned as out-of-equilibrium enzymatic networks encompassed by a selectively open phospholipid bilayer allowing for protein-mediated communication; internal metabolite recycling is another key aspect of a sustainable metabolism. Importantly, gaining tight control over the external medium is essential to avoid thermodynamic equilibrium due to nutrient depletion or waste buildup in a closed compartment (e.g., a test tube). Implementing a sustainable strategy for phospholipid biosynthesis is key to expanding the cellular boundaries. However, phospholipid biosynthesis is currently limited by substrate availability, e.g., of glycerol 3-phosphate, the essential core of phospholipid headgroups. Here, we reconstitute an enzymatic network for sustainable glycerol 3-phosphate synthesis inside large unilamellar vesicles. We exploit the Escherichia coli glycerol kinase GlpK to synthesize glycerol 3-phosphate from externally supplied glycerol. We fuel phospholipid headgroup formation by sustainable l-arginine breakdown. In addition, we design and characterize a dynamic dialysis setup optimized for synthetic cells, which is used to control the external medium composition and to achieve sustainable glycerol 3-phosphate synthesis.

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.

Adaptive laboratory evolution of Escherichia coli W enhances gamma-aminobutyric acid production using glycerol as the carbon source

The microbial conversion of glycerol into value-added commodity products has emerged as an attractive means to meet the demands of biosustainability. However, glycerol is a non-preferential carbon source for productive fermentation because of its low energy density. We employed evolutionary and metabolic engineering in tandem to construct an Escherichia coli strain with improved GABA production using glycerol as the feedstock carbon. Adaptive evolution of E. coli W under glycerol-limited conditions for 1300 generations harnessed an adapted strain with a metabolic system optimized for glycerol utilization. Mutation profiling, enzyme kinetic assays, and transcriptome analysis of the adapted strain allowed us to decipher the basis of glycerol adaptation at the molecular level. Importantly, increased substrate influx mediated by the mutant glpK and modulation of intracellular cAMP levels were the key drivers of improved fitness in the glycerol-limited condition. Leveraging the enhanced capability of glycerol utilization in the strain, we constructed a GABA-producing E. coli W-derivative with superior GABA production compared to the wild-type. Furthermore, rationally designed inactivation of the non-essential metabolic genes, including ackA, mgsA, and gabT, in the glycerol-adapted strain improved the final GABA titer and specific productivity by 3.9- and 4.3-fold, respectively, compared with the wild-type.

Sustainable biosynthesis of chemicals from methane and glycerol via reconstruction of multi-carbon utilizing pathway in obligate methanotrophic bacteria

Obligate methanotrophic bacteria can utilize methane, an inexpensive carbon feedstock, as a sole energy and carbon substrate, thus are considered as the only nature-provided biocatalyst for sustainable biomanufacturing of fuels and chemicals from methane. To address the limitation of native C1 metabolism of obligate type I methanotrophs, we proposed a novel platform strain that can utilize methane and multi-carbon substrates, such as glycerol, simultaneously to boost growth rates and chemical production in Methylotuvimicrobium alcaliphilum 20Z. To demonstrate the uses of this concept, we reconstructed a 2,3-butanediol biosynthetic pathway and achieved a fourfold higher titer of 2,3-butanediol production by co-utilizing methane and glycerol compared with that of methanotrophic growth. In addition, we reported the creation of a methanotrophic biocatalyst for one-step bioconversion of methane to methanol in which glycerol was used for cell growth, and methane was mainly used for methanol production. After the deletion of genes encoding methanol dehydrogenase (MDH), 11.6 mM methanol was obtained after 72 h using living cells in the absence of any chemical inhibitors of MDH and exogenous NADH source. A further improvement of this bioconversion was attained by using resting cells with a significantly increased titre of 76 mM methanol after 3.5 h with the supply of 40 mM formate. The work presented here provides a novel framework for a variety of approaches in methane-based biomanufacturing.

Enhancing protein perdeuteration by experimental evolution of Escherichia coli K-12 for rapid growth in deuterium-based media

Deuterium is a natural low abundance stable hydrogen isotope that in high concentrations negatively affects growth of cells. Here, we have studied growth of Escherichia coli MG1655, a wild-type laboratory strain of E. coli K-12, in deuterated glycerol minimal medium. The growth rate and final biomass in deuterated medium is substantially reduced compared to cells grown in ordinary medium. By using a multi-generation adaptive laboratory evolution-based approach, we have isolated strains that show increased fitness in deuterium-based growth media. Whole-genome sequencing identified the genomic changes in the obtained strains and show that there are multiple routes to genetic adaptation to growth in deuterium-based media. By screening a collection of single-gene knockouts of nonessential genes, no specific gene was found to be essential for growth in deuterated minimal medium. Deuteration of proteins is of importance for NMR spectroscopy, neutron protein crystallography, neutron reflectometry, and small angle neutron scattering. The laboratory evolved strains, with substantially improved growth rate, were adapted for recombinant protein production by T7 RNA polymerase overexpression systems and shown to be suitable for efficient production of perdeuterated soluble and membrane proteins for structural biology applications.

Hierarchical and simultaneous utilization of carbon substrates: mechanistic insights, physiological roles, and ecological consequences

Bacteria grown on a mixture of carbon substrates exhibit two utilization patterns: hierarchical utilization (HU) and simultaneous utilization (SU). How and why cells adopt these different behaviors remains poorly understood despite decades of research. Recent studies address various open questions from multiple viewpoints. From a mechanistic perspective, it was found that flux sensors play a central role in the regulation of substrate utilization, accounting for the known dependences on single-substrate growth rates, substrate concentrations, and the point where the substrate enters central metabolism. From a physiological perspective, several recent studies suggested HU or SU as growth-optimizing strategies through efficient allocation of essential proteome resources. However, other studies demonstrate that a significant fraction of the proteome is dedicated to functions apparently unnecessary for growth, casting doubt on explanations based on slight efficiency gains. From an ecological perspective, recent theoretical studies suggest that HU can help increase species diversity in bacterial communities.

Highly Efficient Production of N-Acetyl-glucosamine in Escherichia coli by Appropriate Catabolic Division of Labor in the Utilization of Mixed Glycerol/Glucose Carbon Sources

Currently, microbial production is becoming a competitive method for N-acetyl-glucosamine production. As the biosynthesis of N-acetyl-glucosamine originating from fructose-6-P directly competes with central carbon metabolism for precursor supply, the consumption of glucose for cell growth and cellular metabolism severely limits the yield of N-acetyl-glucosamine. In this study, appropriate catabolic division of labor in the utilization of mixed carbon sources was achieved by deleting the pfkA gene and enhancing the utilization of glycerol by introducing the glpK mutant. Glycerol thus mainly contributed to cell growth and cellular metabolism, and more glucose was saved for efficient N-acetyl-glucosamine synthesis. By optimizing the ratio of glycerol to glucose, the balancing of cell growth/cellular metabolism and N-acetyl-glucosamine synthesis was achieved. The resulting strain GLALD-7 produced 179.7 g/L N-acetyl-glucosamine using mixed glycerol/glucose (1:8, m/m) carbon sources in a 5 L bioreactor, with a yield of 0.458 g/g total carbon sources (0.529 g/g glucose) and a productivity of 2.57 g/L/h. Coherent high titer/yield/productivity was obtained, with the highest values ever reported, suggesting that an appropriate catabolic division of labor using mixed glycerol/glucose carbon sources is a useful strategy for facilitating the microbial production of chemicals originating from glucose or metabolites upstream of glycolysis.

A kinetic model of the central carbon metabolism for acrylic acid production in Escherichia coli

Acrylic acid is a value-added chemical used in industry to produce diapers, coatings, paints, and adhesives, among many others. Due to its economic importance, there is currently a need for new and sustainable ways to synthesise it. Recently, the focus has been laid in the use of Escherichia coli to express the full bio-based pathway using 3-hydroxypropionate as an intermediary through three distinct pathways (glycerol, malonyl-CoA, and β-alanine). Hence, the goals of this work were to use COPASI software to assess which of the three pathways has a higher potential for industrial-scale production, from either glucose or glycerol, and identify potential targets to improve the biosynthetic pathways yields. When compared to the available literature, the models developed during this work successfully predict the production of 3-hydroxypropionate, using glycerol as carbon source in the glycerol pathway, and using glucose as a carbon source in the malonyl-CoA and β-alanine pathways. Finally, this work allowed to identify four potential over-expression targets (glycerol-3-phosphate dehydrogenase (G3pD), acetyl-CoA carboxylase (AccC), aspartate aminotransferase (AspAT), and aspartate carboxylase (AspC)) that should, theoretically, result in higher AA yields.

Rewiring of glycerol metabolism in Escherichia coli for effective production of recombinant proteins

BACKGROUND

The economic viability of a protein-production process relies highly on the production titer and the price of raw materials. Crude glycerol coming from the production of biodiesel is a renewable and cost-effective resource. However, glycerol is inefficiently utilized by Escherichia coli.

RESULTS

This issue was addressed by rewiring glycerol metabolism for redistribution of the metabolic flux. Key steps in central metabolism involving the glycerol dissimilation pathway, the pentose phosphate pathway, and the tricarboxylic acid cycle were pinpointed and manipulated to provide precursor metabolites and energy. As a result, the engineered E. coli strain displayed a 9- and 30-fold increase in utilization of crude glycerol and production of the target protein, respectively.

CONCLUSIONS

The result indicates that the present method of metabolic engineering is useful and straightforward for efficient adjustment of the flux distribution in glycerol metabolism. The practical application of this methodology in biorefinery and the related field would be acknowledged.

Causal mutations from adaptive laboratory evolution are outlined by multiple scales of genome annotations and condition-specificity

BACKGROUND

Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover mutations that confer phenotypic functions of interest. However, the task of finding and understanding all beneficial mutations of an ALE experiment remains an open challenge for the field. To provide for better results than traditional methods of ALE mutation analysis, this work applied enrichment methods to mutations described by a multiscale annotation framework and a consolidated set of ALE experiment conditions. A total of 25,321 unique genome annotations from various sources were leveraged to describe multiple scales of mutated features in a set of 35 Escherichia coli based ALE experiments. These experiments totalled 208 independent evolutions and 2641 mutations. Additionally, mutated features were statistically associated across a total of 43 unique experimental conditions to aid in deconvoluting mutation selection pressures.

RESULTS

Identifying potentially beneficial, or key, mutations was enhanced by seeking coding and non-coding genome features significantly enriched by mutations across multiple ALE replicates and scales of genome annotations. The median proportion of ALE experiment key mutations increased from 62%, with only small coding and non-coding features, to 71% with larger aggregate features. Understanding key mutations was enhanced by considering the functions of broader annotation types and the significantly associated conditions for key mutated features. The approaches developed here were used to find and characterize novel key mutations in two ALE experiments: one previously unpublished with Escherichia coli grown on glycerol as a carbon source and one previously published with Escherichia coli tolerized to high concentrations of L-serine.

CONCLUSIONS

The emergent adaptive strategies represented by sets of ALE mutations became more clear upon observing the aggregation of mutated features across small to large scale genome annotations. The clarification of mutation selection pressures among the many experimental conditions also helped bring these strategies to light. This work demonstrates how multiscale genome annotation frameworks and data-driven methods can help better characterize ALE mutations, and thus help elucidate the genotype-to-phenotype relationship of the studied organism.

Proteomic Analyses Reveal New Insights on the Antimicrobial Mechanisms of Chitosan Biopolymers and Their Nanosized Particles against Escherichia coli

The well-known antimicrobial effects of chitosan (CS) polymers make them a promising adjuvant in enhancing antibiotic effectiveness against human pathogens. However, molecular CS antimicrobial mechanisms remain unclear, despite the insights presented in the literature. Thus, the aim of the present study was to depict the molecular effects implicated in the interaction of low or medium molecular mass CS polymers and their nanoparticle-counterparts against Escherichia coli. The differential E. coli proteomes sensitized to either CS polymers or nanoparticles were investigated by nano liquid chromatography–mass spectrometry (micro-LC-MS/MS). A total of 127 proteins differentially expressed in CS-sensitized bacteria were predominantly involved in (i) structural functions associated to the stability of outer membrane, (ii) increment of protein biosynthesis due to high abundance of ribosomal proteins and (iii) activation of biosynthesis of amino acid and purine metabolism pathways. Antibacterial activity of CS polymers/nanoparticles seems to be triggered by the outer bacterial membrane disassembly, leading to increased protein biosynthesis by diverting the metabolic flux to amino acid and purine nucleotides supply. Understanding CS-antibacterial molecular effects can be valuable to optimize the use of CS-based nanomaterials in food decontamination, and may represent a breakthrough on CS nanocapsules-drug delivery devices for novel antibiotics, as the chitosan-disassembly of bacteria cell membranes can potentialize antibiotic effects.

Cascade synthesis of rare ketoses by whole cells based on L-rhamnulose-1-phosphate aldolase

Dihydroxyacetone phosphate (DHAP)-dependent aldolases demonstrate important values in the production of rare ketoses due to their unique stereoselectivities. As a specific example, we developed an efficient Escherichia coli whole-cell biocatalytic cascade system in which rare ketoses were produced from abundant glycerol and catalyzed by four enzymes based on L-rhamnulose-1-phosphate aldolase (RhaD). For the semicontinuous bioconversion in which D-glyceraldehyde was continuously added, once D-glyceraldehyde was consumed, the final yields of D-sorbose and D-psicose were 15.30 g/L and 6.35 g/L, respectively. Moreover, the maximum conversion rate and productivity of D-sorbose and D-psicose were 99% and 1.11 g/L/h at 8 h, respectively. When L-glyceraldehyde was used instead of the D-isomer, the final yield of L-fructose was 16.80 g/L. Furthermore, the maximum conversion rate and productivity of L-fructose were 95% and 1.08 g/L/h at 8 h, respectively. This synthetic platform was also compatible with other various aldehydes, which allowed the production of many other high-value chemicals from glycerol.

Regulation underlying hierarchical and simultaneous utilization of carbon substrates by flux sensors in Escherichia coli

Many microbes exhibit nutrient preferences, exemplified by the “hierarchical” consumption of certain carbon substrates. Here we systematically investigate under which physiological conditions hierarchical substrate utilization occurs and its mechanisms of implementation. We show utilization hierarchy of Escherichia coli to be ordered by the carbon-uptake flux rather than the identity of the substrates. A detailed study of glycerol uptake finds that it is fully suppressed if the uptake flux of another glycolytic substrate exceeds a threshold, set to the influx obtained when grown on glycerol alone. Below this threshold, limited glycerol uptake is “supplemented” such that the total carbon uptake is maintained at the threshold. This behavior results from total-flux feedback mediated by cAMP-Crp signaling, but also requires inhibition by regulator fructose-1,6-bisphosphate, which senses the upper glycolytic flux and ensures that glycerol uptake defers to other glycolytic substrates but not to gluconeogenic ones. A quantitative model reproduces all observed utilization patterns including those of key mutants. The proposed mechanism relies on differential regulation of uptake enzymes and requires a specific operon organization. This organization is found conserved across related species for several uptake systems, suggesting the deployment of similar mechanisms for hierarchical substrate utilization by a spectrum of microbes.

Biochemistry, genetics and biotechnology of glycerol utilization in Pseudomonas species

The use of renewable waste feedstocks is an environment‐friendly choice contributing to the reduction of waste treatment costs and increasing the economic value of industrial by‐products. Glycerol (1,2,3‐propanetriol), a simple polyol compound widely distributed in biological systems, constitutes a prime example of a relatively cheap and readily available substrate to be used in bioprocesses. Extensively exploited as an ingredient in the food and pharmaceutical industries, glycerol is also the main by‐product of biodiesel production, which has resulted in a progressive drop in substrate price over the years. Consequently, glycerol has become an attractive substrate in biotechnology, and several chemical commodities currently produced from petroleum have been shown to be obtained from this polyol using whole‐cell biocatalysts with both wild‐type and engineered bacterial strains. Pseudomonas species, endowed with a versatile and rich metabolism, have been adopted for the conversion of glycerol into value‐added products (ranging from simple molecules to structurally complex biopolymers, e.g. polyhydroxyalkanoates), and a number of metabolic engineering strategies have been deployed to increase the number of applications of glycerol as a cost‐effective substrate. The unique genetic and metabolic features of glycerol‐grown Pseudomonas are presented in this review, along with relevant examples of bioprocesses based on this substrate – and the synthetic biology and metabolic engineering strategies implemented in bacteria of this genus aimed at glycerol valorization.

DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression

BACKGROUND

Genome-scale models of metabolism and macromolecular expression (ME models) enable systems-level computation of proteome allocation coupled to metabolic phenotype.

RESULTS

We develop DynamicME, an algorithm enabling time-course simulation of cell metabolism and protein expression. DynamicME correctly predicted the substrate utilization hierarchy on a mixed carbon substrate medium. We also found good agreement between predicted and measured time-course expression profiles. ME models involve considerably more parameters than metabolic models (M models). We thus generate an ensemble of models (each model having its rate constants perturbed), and then analyze the models by identifying archetypal time-course metabolite concentration profiles. Furthermore, we use a metaheuristic optimization method to calibrate ME model parameters using time-course measurements such as from a (fed-) batch culture. Finally, we show that constraints on protein concentration dynamics ("inertia") alter the metabolic response to environmental fluctuations, including increased substrate-level phosphorylation and lowered oxidative phosphorylation.

CONCLUSIONS

Overall, DynamicME provides a novel method for understanding proteome allocation and metabolism under complex and transient environments, and to utilize time-course cell culture data for model-based interpretation or model refinement.

Microalgae for the production of lipid and carotenoids: a review with focus on stress regulation and adaptation

Microalgae have drawn great attention as promising sustainable source of lipids and carotenoids. Their lipid and carotenoids accumulation machinery can be trigged by the stress conditions such as nutrient limitation or exposure to the damaging physical factors. However, stressful conditions often adversely affect microalgal growth and cause oxidative damage to the cells, which can eventually reduce the yield of the desired products. To overcome these limitations, two-stage cultivation strategies and supplementation of growth-promoting agents have traditionally been utilized, but developing new highly adapted strains is theoretically the simplest strategy. In addition to genetic engineering, adaptive laboratory evolution (ALE) is frequently used to develop beneficial phenotypes in industrial microorganisms during long-term selection under specific stress conditions. In recent years, many studies have gradually introduced ALE as a powerful tool to improve the biological properties of microalgae, especially for improving the production of lipid and carotenoids. In this review, strategies for the manipulation of stress in microalgal lipids and carotenoids production are summarized and discussed. Furthermore, this review summarizes the overall state of ALE technology, including available selection pressures, methods, and their applications in microalgae for the improved production of lipids and carotenoids.

Metabolome and molecular basis for carbohydrate increase and nitrate reduction in burley tobacco seedlings by glycerol through upregulating carbon and nitrogen metabolism

Burley tobacco (Nicotiana Tabacum) is a chlorophyll-deficiency mutant. Nitrate is one precursor of tobacco-specific nitrosamines (TSNAs) and is largely accumulated in burley tobacco. To decrease nitrate accumulation in burley tobacco, glycerol, a polyhydric alcohol compound and physiological regulating material, was sprayed and its effects were investigated based on metabolomic technology and molecular biology. The results showed that glucose, glutamine and glutamic acid increased by 2.6, 5.1 and 196, folds, respectively, in tobacco leaves after glycerol application. Nitrate content was significantly decreased by 12-16% and expression of eight genes responsible for carbon and nitrogen metabolism were up-regulated with glycerol applications under both normal and 20% reduced nitrogen levels (P < 0.01). Leaf biomass of plants sprayed with glycerol and 20% nitrogen reduction was equivalent to that of no glycerol control with normal nitrogen application. Carbohydrates biosynthesis, nitrate transport and nitrate assimilation were enhanced in glycerol sprayed burley tobacco seedlings which might contribute to reduced nitrate and increased carbohydrates contents. In conclusion, glyerol spray coupled with 20% nitrogen reduction would be an effective method to reduce nitrate accumulation in burley tobacco.

Genetic Adaptation to Growth Under Laboratory Conditions in Escherichia coli and Salmonella enterica

Experimental evolution under controlled laboratory conditions is becoming increasingly important to address various evolutionary questions, including, for example, the dynamics and mechanisms of genetic adaptation to different growth and stress conditions. In such experiments, mutations typically appear that increase the fitness under the conditions tested (medium adaptation), but that are not necessarily of interest for the specific research question. Here, we have identified mutations that appeared during serial passage of E. coli and S. enterica in four different and commonly used laboratory media and measured the relative competitive fitness and maximum growth rate of 111 genetically re-constituted strains, carrying different single and multiple mutations. Little overlap was found between the mutations that were selected in the two species and the different media, implying that adaptation occurs via different genetic pathways. Furthermore, we show that commonly occurring adaptive mutations can generate undesired genetic variation in a population and reduce the accuracy of competition experiments. However, by introducing media adaptation mutations with large effects into the parental strain that was used for the evolution experiment, the variation (standard deviation) was decreased 10-fold, and it was possible to measure fitness differences between two competitors as small as |s| < 0.001.

Sexual recombination and increased mutation rate expedite evolution of Escherichia coli in varied fitness landscapes

Sexual recombination and mutation rate are theorized to play different roles in adaptive evolution depending on the fitness landscape; however, direct experimental support is limited. Here we examine how these factors affect the rate of adaptation utilizing a “genderless” strain of Escherichia coli capable of continuous in situ sexual recombination. The results show that the populations with increased mutation rate, and capable of sexual recombination, outperform all the other populations. We further characterize two sexual and two asexual populations with increased mutation rate and observe maintenance of beneficial mutations in the sexual populations through mutational sweeps. Furthermore, we experimentally identify the molecular signature of a mating event within the sexual population that combines two beneficial mutations to generate a fitter progeny; this evidence suggests that the recombination event partially alleviates clonal interference. We present additional data suggesting that stochasticity plays an important role in the combinations of mutations observed.

Sexual recombination and mutation rate may play different roles in adaptive evolution depending on the fitness landscape. Here, Peabody et al. examine how the two factors affect the rate of adaptation of an E. coli strain capable of sexual recombination, under different conditions during experimental evolution.

ArcA overexpression induces fermentation and results in enhanced growth rates of E. coli

Overflow metabolism in the presence of oxygen occurs at fast growth rates in a wide range of organisms including bacteria, yeast and cancer cells and plays an important role in biotechnology during production of proteins or metabolic compounds. As recently suggested, overflow metabolism can be understood in terms of proteome allocation, since fermentation has lower proteome cost for energy production than respiration. Here, we demonstrate that ArcA overexpression in aerobic conditions, results in downregulation of respiratory pathways and enhanced growth rates on glycolytic substrates of E. coli, coinciding with acetate excretion and increased carbon uptake rates. These results suggest that fermentation enables faster growth and demonstrate that fermentation on many glycolytic carbon sources is not limited by carbon uptake. Hence, these findings are difficult to reconcile with many alternative hypotheses that have been proposed for the origin of overflow metabolism and the growth rate dependence of fermentation and respiration, which are based on limited capacity of respiration or limitations in uptake rates and catabolic pathways. Instead, as suggested by increased lag phases of ArcA overexpression strains, respiratory energy metabolism may be related to a general preparatory response, observed for decreasing growth rates, but with limited advantages for maximizing steady-state growth rate.

Optimality and sub-optimality in a bacterial growth law

Organisms adjust their gene expression to improve fitness in diverse environments. But finding the optimal expression in each environment presents a challenge. We ask how good cells are at finding such optima by studying the control of carbon catabolism genes in Escherichia coli. Bacteria show a growth law: growth rate on different carbon sources declines linearly with the steady-state expression of carbon catabolic genes. We experimentally modulate gene expression to ask if this growth law always maximizes growth rate, as has been suggested by theory. We find that the growth law is optimal in many conditions, including a range of perturbations to lactose uptake, but provides sub-optimal growth on several other carbon sources. Combining theory and experiment, we genetically re-engineer E. coli to make sub-optimal conditions into optimal ones and vice versa. We conclude that the carbon growth law is not always optimal, but represents a practical heuristic that often works but sometimes fails.

Organisms improve their fitness by adjusting their gene expression to the environment, for example bacteria scale the expression of metabolic enzymes near linearly to their growth rate. Here, the authors show that such linear scaling often maximizes growth rate, but that linear scaling is suboptimal under some conditions.

Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments

The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs on cellular growth rates; however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change.

An overarching endeavor in systems biology is to characterize and understand the allocation of an organism’s proteome. Common approaches to characterize proteome allocation are based on annotations of protein functions or transcriptional regulatory targets. Here, we develop a novel approach based on model-predicted proteome utilization. This approach reveals that in many environments, a large fraction of the proteome is unused. Unused protein expression is known to incur costs on organismal fitness. We show that changes in the allocation of the proteome to used versus unused fractions can account for the variability in growth rates observed across environments and is a common mechanism to increase growth rates in laboratory evolution experiments. We compare our approach to classify the proteome based on model-predicted utilization to more traditional approaches to reveal biological functions and transcriptional regulators underlying the expression of unused protein. Expression of these functions may reflect ecological trade-offs between growth, nutrient-readiness, and stress resistance.

Overflow metabolism in Escherichia coli results from efficient proteome allocation

Overflow metabolism refers to the seemingly wasteful strategy in which cells use fermentation instead of the more efficient respiration to generate energy, despite the availability of oxygen. Known as Warburg effect in the context of cancer growth, this phenomenon occurs ubiquitously for fast growing cells, including bacteria, fungi, and mammalian cells, but its origin has remained mysterious despite decades of research. Here we study metabolic overflow in E. coli and show that it is a global physiological response used to cope with changing proteomic demands of energy biogenesis and biomass synthesis under different growth conditions. A simple model of proteomic resource allocation can quantitatively account for all of the observed behaviors and accurately predict responses to novel perturbations. The key hypothesis of the model, that the proteome cost of energy biogenesis by respiration exceeds that by fermentation, is quantitatively confirmed by direct measurement of protein abundances via quantitative mass spectrometry.

Elucidation of the co-metabolism of glycerol and glucose in Escherichia coli by genetic engineering, transcription profiling, and (13)C metabolic flux analysis

BACKGROUND

Glycerol, a byproduct of biodiesel, has become a readily available and inexpensive carbon source for the production of high-value products. However, the main drawback of glycerol utilization is the low consumption rate and shortage of NADPH formation, which may limit the production of NADPH-requiring products. To overcome these problems, we constructed a carbon catabolite repression-negative ΔptsGglpK* mutant by both blocking a key glucose PTS transporter and enhancing the glycerol conversion. The mutant can recover normal growth by co-utilization of glycerol and glucose after loss of glucose PTS transporter. To reveal the metabolic potential of the ΔptsGglpK* mutant, this study examined the flux distributions and regulation of the co-metabolism of glycerol and glucose in the mutant.

RESULTS

By labeling experiments using [1,3-(13)C]glycerol and [1-(13)C]glucose, (13)C metabolic flux analysis was employed to decipher the metabolisms of both the wild-type strain and the ΔptsGglpK* mutant in chemostat cultures. When cells were maintained at a low dilution rate (0.1 h(-1)), the two strains showed similar fluxome profiles. When the dilution rate was increased, both strains upgraded their pentose phosphate pathway, glycolysis and anaplerotic reactions, while the ΔptsGglpK* mutant was able to catabolize much more glycerol than glucose (more than tenfold higher). Compared with the wild-type strain, the mutant repressed its flux through the TCA cycle, resulting in higher acetate overflow. The regulation of fluxomes was consistent with transcriptional profiling of several key genes relevant to the TCA cycle and transhydrogenase, namely gltA, icdA, sdhA and pntA. In addition, cofactor fluxes and their pool sizes were determined. The ΔptsGglpK* mutant affected the redox NADPH/NADH state and reduced the ATP level. Redox signaling activated the ArcA regulatory system, which was responsible for TCA cycle repression.

CONCLUSIONS

This work employs both (13)C-MFA and transcription/metabolite analysis for quantitative investigation of the co-metabolism of glycerol and glucose in the ΔptsGglpK* mutant. The ArcA regulatory system dominates the control of flux redistribution. The ΔptsGglpK* mutant can be used as a platform for microbial cell factories for the production of biofuels and biochemicals, since most of fuel molecule (e.g., alcohols) synthesis requires excess reducing equivalents.

Systems-level response to point mutations in a core metabolic enzyme modulates genotype-phenotype relationship

Linking the molecular effects of mutations to fitness is central to understanding evolutionary dynamics. Here, we establish a quantitative relation between the global effect of mutations on the E. coli proteome and bacterial fitness. We created E. coli strains with specific destabilizing mutations in the chromosomal folA gene encoding dihydrofolate reductase (DHFR) and quantified the ensuing changes in the abundances of 2,000+ E. coli proteins in mutant strains using tandem mass tags with subsequent LC-MS/MS. mRNA abundances in the same E. coli strains were also quantified. The proteomic effects of mutations in DHFR are quantitatively linked to phenotype: the SDs of the distributions of logarithms of relative (to WT) protein abundances anticorrelate with bacterial growth rates. Proteomes hierarchically cluster first by media conditions, and within each condition, by the severity of the perturbation to DHFR function. These results highlight the importance of a systems-level layer in the genotype-phenotype relationship.

Metabolic Regulation and Coordination of the Metabolism in Bacteria in Response to a Variety of Growth Conditions

Living organisms have sophisticated but well-organized regulation system. It is important to understand the metabolic regulation mechanisms in relation to growth environment for the efficient design of cell factories for biofuels and biochemicals production. Here, an overview is given for carbon catabolite regulation, nitrogen regulation, ion, sulfur, and phosphate regulations, stringent response under nutrient starvation as well as oxidative stress regulation, redox state regulation, acid-shock, heat- and cold-shock regulations, solvent stress regulation, osmoregulation, and biofilm formation, and quorum sensing focusing on Escherichia coli metabolism and others. The coordinated regulation mechanisms are of particular interest in getting insight into the principle which governs the cell metabolism. The metabolism is controlled by both enzyme-level regulation and transcriptional regulation via transcription factors such as cAMP-Crp, Cra, Csr, Fis, P(II)(GlnB), NtrBC, CysB, PhoR/B, SoxR/S, Fur, MarR, ArcA/B, Fnr, NarX/L, RpoS, and (p)ppGpp for stringent response, where the timescales for enzyme-level and gene-level regulations are different. Moreover, multiple regulations are coordinated by the intracellular metabolites, where fructose 1,6-bisphosphate (FBP), phosphoenolpyruvate (PEP), and acetyl-CoA (AcCoA) play important roles for enzyme-level regulation as well as transcriptional control, while α-ketoacids such as α-ketoglutaric acid (αKG), pyruvate (PYR), and oxaloacetate (OAA) play important roles for the coordinated regulation between carbon source uptake rate and other nutrient uptake rate such as nitrogen or sulfur uptake rate by modulation of cAMP via Cya.

Distinctive protein expression patterns of the strain Brevundimonas sp. ZF12 isolated from the aqueous zone containing high levels of radiation to cadmium-induced stress

In the current study, different protein expression profiles in a strain Brevundimonas sp. ZF12, isolated from the aqueous zone containing high levels of radiation, were characterized following exposure to cadmium (II) using a proteomic strategy. In order to gain a deeper understanding of the cellular events that allow this strain to survive and undergo cadmium adaptation and sorption, the strain was tested under three experimental conditions of 5, 10 and 30 ppm cadmium (II) ions stress. Two-dimensional polyacrylamide gel electrophoresis and mass spectrometry were used to identify the differentially expressed proteins under cadmium (II) stress. 20 differentially expressed spots were successfully identified by MS/MS analysis. These proteins are involved in DNA repair and protection, amino acid metabolism, nucleotide metabolism, energy homeostasis, oxidative stress response, redox homeostasis, protein folding and heat-shock response. The results obviously indicate that the ZF12 strain tends to endure the cadmium (II) stress conditions by modification in many aspects of its cellular physiology and metabolism.

Ex uno plures: clonal reinforcement drives evolution of a simple microbial community

A major goal of genetics is to define the relationship between phenotype and genotype, while a major goal of ecology is to identify the rules that govern community assembly. Achieving these goals by analyzing natural systems can be difficult, as selective pressures create dynamic fitness landscapes that vary in both space and time. Laboratory experimental evolution offers the benefit of controlling variables that shape fitness landscapes, helping to achieve both goals. We previously showed that a clonal population of E. coli experimentally evolved under continuous glucose limitation gives rise to a genetically diverse community consisting of one clone, CV103, that best scavenges but incompletely utilizes the limiting resource, and others, CV101 and CV116, that consume its overflow metabolites. Because this community can be disassembled and reassembled, and involves cooperative interactions that are stable over time, its genetic diversity is sustained by clonal reinforcement rather than by clonal interference. To understand the genetic factors that produce this outcome, and to illuminate the community's underlying physiology, we sequenced the genomes of ancestral and evolved clones. We identified ancestral mutations in intermediary metabolism that may have predisposed the evolution of metabolic interdependence. Phylogenetic reconstruction indicates that the lineages that gave rise to this community diverged early, as CV103 shares only one Single Nucleotide Polymorphism with the other evolved clones. Underlying CV103's phenotype we identified a set of mutations that likely enhance glucose scavenging and maintain redox balance, but may do so at the expense of carbon excreted in overflow metabolites. Because these overflow metabolites serve as growth substrates that are differentially accessible to the other community members, and because the scavenging lineage shares only one SNP with these other clones, we conclude that this lineage likely served as an “engine” generating diversity by creating new metabolic niches, but not the occupants themselves.

The variability of natural systems makes it difficult to deduce how organisms' genotypes manifest as phenotypes, and how communities of interacting organisms arise. Using laboratory experimental evolution we can control this variation. We previously showed that a population of E. coli that originated from a single clone and was cultured in the presence of a single limiting resource, evolves into a stable, three-membered community, wherein one clone excretes metabolites that the others utilize as carbon sources. To discern the genetic factors at work in producing this outcome and to illuminate the community's physiology, we sequenced the genomes of the ancestral and evolved clones. We identified in the ancestor mutations that may have predisposed evolution of cross-feeding. We found that the lineages which gave rise to the community diverged early on, and that the numerically dominant lineage that best scavenges limiting glucose does so as a result of adaptive mutations that enhance glucose uptake but favor fermentative over respiratory pathways, resulting in overflow metabolites. Because this clone produces secondary resources that sustain other community members, and because it shares with them only one mutation, we conclude that it is an “engine” generating diversity by creating new niches, but not the occupants themselves.

Antibiotic-free segregational plasmid stabilization in Escherichia coli owing to the knockout of triosephosphate isomerase (tpiA)

Background

Segregational stability of plasmids is of major concern for recombinant bacterial production strains. One of the best strategies to counteract plasmid loss is the use of auxotrophic mutants which are complemented with the lacking gene along with the product-relevant ones. However, these knockout mutants often show unwanted growth in complex standard media or no growth at all under uncomplemented conditions. This led to the choice of a gene for knockout that only connects two essential arms of an essential metabolic pathway – the glycolysis.

Results

Triosephosphate isomerase was chosen because its knockout will have a tremendous effect on growth on glucose as well as on glycerol. On glycerol the effect is almost absolute whereas on glucose growth is still possible, but with considerably lower rate than usual. This feature is essential because it may render cloning easier. This enzymatic activity was successfully tested as an alternative to antibiotic-based plasmid selection. Expression of a model recombinant β-glucanase in continuous cultivation was possible with stable maintenance of the plasmid. In addition, the complementation of tpiA knockout strains by the corresponding plasmids and their growth characteristics were tested on a series of complex and synthetic media. The accumulation of methylglyoxal during the growth of tpiA-deficient strains was shown to be a possible cause for the growth disadvantage of these strains in comparison to the parent strain for the Keio Collection strain or the complemented knock-out strain.

Conclusion

Through the use of this new auxotrophic complementation system, antibiotic-free cloning and selection of recombinant plasmid were possible. Continuous cultivation and recombinant protein expression with high segregational stability over an extended time period was also demonstrated.

Evolutionary history and genetic parallelism affect correlated responses to evolution

We investigated the relationship between genomic and phenotypic evolution among replicate populations of Escherichia coli evolved for 1000 generations in four different environments. By resequencing evolved genomes, we identified parallel changes in genes encoding transcription regulators within and between environments. Depending on both the environment and the altered gene, genetic parallelism at the gene level involved mutations that affected identical codons, protein domains or were widely distributed across the gene. Evolved clones were characterized by parallel phenotypic changes in their respective evolution environments but also in the three alternative environments. Phenotypic parallelism was high for clones that evolved in the same environment, even in the absence of genetic parallelism. By contrast, clones that evolved in different environments revealed a higher parallelism in correlated responses when they shared mutated genes. Altogether, this work shows that after an environmental change or the colonization of a new habitat, similar ecological performance might be expected from individuals that share mutated genes or that experienced similar past selective pressures.

The reproducibility of adaptation in the light of experimental evolution with whole genome sequencing

A key question in evolutionary biology is the reproducibility of adaptation. This question can now be quantitatively analyzed using experimental evolution coupled to whole genome sequencing (WGS). With complete sequence data, one can assess convergence among replicate populations. In turn, convergence reflects the action of natural selection and also the breadth of the field of possible adaptive solutions. That is, it provides insight into how many genetic solutions or adaptive paths may lead to adaptation in a given environment. Convergence is both a property of an adaptive landscape and, reciprocally, a tool to study that landscape. In this chapter we present the links between convergence and the properties of adaptive landscapes with respect to two types of microbial experimental evolution. The first tries to reconstruct a full adaptive landscape using a handful of carefully identified mutations (the reductionist approach), while the second uses WGS of replicate experiments to infer properties of the adaptive landscape. Reductionist approaches have highlighted the importance of epistasis in shaping the adaptive landscape, but have also uncovered a wide diversity of landscape architectures. The WGS approach has uncovered a very high diversity of beneficial mutations that affect a limited set of genes or functions and also suggests some shortcomings of the reductionist approach. We conclude that convergence may be better defined at an integrated level, such as the genic level or even at a phenotypic level, and that integrated mechanistic models derived from systems biology may offer an interesting perspective for the analysis of convergence at all levels.

Kinetic models reveal the in vivo mechanisms of mutagenesis in microbes and man

This review summarizes the evidence indicating that mutagenic mechanisms in vivo are essentially the same in all living cells. Unique metabolic reactions to a particular environmental stress apparently target specific genes for increased rates of transcription and mutation, resulting in higher mutation rates for those genes most likely to solve the problem. Kinetic models which have demonstrated predictive value are described and are shown to simulate mutagenesis in vivo in Escherichia coli, the p53 tumor suppressor gene, and somatic hypermutation. In all three models, direct correlations are seen between mutation frequencies and transcription rates. G and C nucleosides in single-stranded DNA (ssDNA) are intrinsically mutable, and G and C silent mutations in p53 and in VH framework regions provide compelling evidence for intrinsic mechanisms of mutability, since mutation outcomes are neutral and are not selected. During transcription, the availability of unpaired bases in the ssDNA of secondary structures is rate-limiting for, and determines the frequency of mutations in vivo. In vitro analyses also verify the conclusion that intrinsically mutable bases are in fact located in ssDNA loops of predicted stem-loop structures (SLSs).

Adaptive regulatory substitutions affect multiple stages in the life cycle of the bacteriophage φX174

BACKGROUND

Previously, we showed that adaptive substitutions in one of the three promoters of the bacteriophage φX174 improved fitness at high-temperature by decreasing transcript levels three- to four-fold. To understand how such an extreme change in gene expression might lead to an almost two-fold increase in fitness at the adaptive temperature, we focused on stages in the life cycle of the phage that occur before and after the initiation of transcription. For both the ancestral strain and two single-substitution strains with down-regulated transcription, we measured seven phenotypic components of fitness (attachment, ejection, eclipse, virion assembly, latent period, lysis rate and burst size) during a single cycle of infection at each of two temperatures. The lower temperature, 37°C, is the optimal temperature at which phages are cultivated in the lab; the higher temperature, 42°C, exerts strong selection and is the condition under which these substitutions arose in evolution experiments. We augmented this study by developing an individual-based stochastic model of this same life cycle to explore potential explanations for our empirical results.

RESULTS

Of the seven fitness parameters, three showed significant differences between strains that carried an adaptive substitution and the ancestor, indicating the presence of pleiotropy in regulatory evolution. 1) Eclipse was longer in the adaptive strains at both the optimal and high-temperature environments. 2) Lysis rate was greater in the adaptive strains at the high temperature. 3) Burst size for the mutants was double that of the ancestor at the high temperature, but half that at the lower temperature. Simulation results suggest that eclipse length and latent period variance can explain differences in burst sizes and fitness between the mutant and ancestral strains.

CONCLUSIONS

Down-regulating transcription affects several steps in the phage life cycle, and all of these occur after the initiation of transcription. We attribute the apparent tradeoff between delayed progeny production and faster progeny release to improved host resource utilization at high temperature.

Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype-phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large-scale network models with sufficient accuracy.

Analyzing the genomic variation of microbial cell factories in the era of "New Biotechnology"

The application of genome-scale technologies, both experimental and in silico, to industrial biotechnology has allowed improving the conversion of biomass-derived feedstocks to chemicals, materials and fuels through microbial fermentation. In particular, due to rapidly decreasing costs and its suitability for identifying the genetic determinants of a phenotypic trait of interest, whole genome sequencing is expected to be one of the major driving forces in industrial biotechnology in the coming years. We present some of the recent studies that have successfully applied high-throughput sequencing technologies for finding the underlying molecular mechanisms for (a) improved carbon source utilization, (b) increased product formation, and (c) stress tolerance. We also discuss the strengths and weaknesses of different strategies for mapping industrially relevant genotype-to-phenotype links including exploiting natural diversity in natural isolates or crosses between isolates, classical mutagenesis and evolutionary engineering.