scholarly journals Description and Interpretation of Adaptive Evolution of Escherichia coli K-12 MG1655 by Using a Genome-Scale In Silico Metabolic Model

2003 ◽  
Vol 185 (21) ◽  
pp. 6400-6408 ◽  
Author(s):  
Stephen S. Fong ◽  
Jennifer Y. Marciniak ◽  
Bernhard Ø. Palsson
Keyword(s):  
Escherichia Coli ◽  
Adaptive Evolution ◽  
Growth Rates ◽  
In Silico ◽  
A Priori ◽  
E Coli ◽  
End Point ◽  
In Silico Model ◽  
Uptake Rates ◽  
Genome Scale

ABSTRACT Genome-scale in silico metabolic networks of Escherichia coli have been reconstructed. By using a constraint-based in silico model of a reconstructed network, the range of phenotypes exhibited by E. coli under different growth conditions can be computed, and optimal growth phenotypes can be predicted. We hypothesized that the end point of adaptive evolution of E. coli could be accurately described a priori by our in silico model since adaptive evolution should lead to an optimal phenotype. Adaptive evolution of E. coli during prolonged exponential growth was performed with M9 minimal medium supplemented with 2 g of α-ketoglutarate per liter, 2 g of lactate per liter, or 2 g of pyruvate per liter at both 30 and 37°C, which produced seven distinct strains. The growth rates, substrate uptake rates, oxygen uptake rates, by-product secretion patterns, and growth rates on alternative substrates were measured for each strain as a function of evolutionary time. Three major conclusions were drawn from the experimental results. First, adaptive evolution leads to a phenotype characterized by maximized growth rates that may not correspond to the highest biomass yield. Second, metabolic phenotypes resulting from adaptive evolution can be described and predicted computationally. Third, adaptive evolution on a single substrate leads to changes in growth characteristics on other substrates that could signify parallel or opposing growth objectives. Together, the results show that genome-scale in silico metabolic models can describe the end point of adaptive evolution a priori and can be used to gain insight into the adaptive evolutionary process for E. coli.

scholarly journals Genome-Scale Analysis of the Uses of the Escherichia coli Genome: Model-Driven Analysis of Heterogeneous Data Sets

2003 ◽  
Vol 185 (21) ◽  
pp. 6392-6399 ◽  
Author(s):  
Timothy E. Allen ◽  
Markus J. Herrgård ◽  
Mingzhu Liu ◽  
Yu Qiu ◽  
Jeremy D. Glasner ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Protein Synthesis ◽  
In Silico ◽  
Half Life ◽  
Data Sets ◽  
Expression Data ◽  
E Coli ◽  
Model Driven ◽  
Life Data ◽  
Genome Scale

ABSTRACT The recent availability of heterogeneous high-throughput data types has increased the need for scalable in silico methods with which to integrate data related to the processes of regulation, protein synthesis, and metabolism. A sequence-based framework for modeling transcription and translation in prokaryotes has been established and has been extended to study the expression state of the entire Escherichia coli genome. The resulting in silico analysis of the expression state highlighted three facets of gene expression in E. coli: (i) the metabolic resources required for genome expression and protein synthesis were found to be relatively invariant under the conditions tested; (ii) effective promoter strengths were estimated at the genome scale by using global mRNA abundance and half-life data, revealing genes subject to regulation under the experimental conditions tested; and (iii) large-scale genome location-dependent expression patterns with approximately 600-kb periodicity were detected in the E. coli genome based on the 49 expression data sets analyzed. These results support the notion that a structured model-driven analysis of expression data yields additional information that can be subjected to commonly used statistical analyses. The integration of heterogeneous genome-scale data (i.e., sequence, expression data, and mRNA half-life data) is readily achieved in the context of an in silico model.

scholarly journals Metabolic Engineering of Escherichia coli for Enhanced Production of Succinic Acid, Based on Genome Comparison and In Silico Gene Knockout Simulation

2005 ◽  
Vol 71 (12) ◽  
pp. 7880-7887 ◽  
Author(s):  
Sang Jun Lee ◽  
Dong-Yup Lee ◽  
Tae Yong Kim ◽  
Byung Hun Kim ◽  
Jinwon Lee ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Succinic Acid ◽  
In Silico ◽  
Acid Production ◽  
Gene Knockout ◽  
Fermentation Products ◽  
E Coli ◽  
Metabolic Analysis ◽  
Enhanced Production ◽  
Succinic Acid Production

ABSTRACT Comparative analysis of the genomes of mixed-acid-fermenting Escherichia coli and succinic acid-overproducing Mannheimia succiniciproducens was carried out to identify candidate genes to be manipulated for overproducing succinic acid in E. coli. This resulted in the identification of five genes or operons, including ptsG, pykF, sdhA, mqo, and aceBA, which may drive metabolic fluxes away from succinic acid formation in the central metabolic pathway of E. coli. However, combinatorial disruption of these rationally selected genes did not allow enhanced succinic acid production in E. coli. Therefore, in silico metabolic analysis based on linear programming was carried out to evaluate the correlation between the maximum biomass and succinic acid production for various combinatorial knockout strains. This in silico analysis predicted that disrupting the genes for three pyruvate forming enzymes, ptsG, pykF, and pykA, allows enhanced succinic acid production. Indeed, this triple mutation increased the succinic acid production by more than sevenfold and the ratio of succinic acid to fermentation products by ninefold. It could be concluded that reducing the metabolic flux to pyruvate is crucial to achieve efficient succinic acid production in E. coli. These results suggest that the comparative genome analysis combined with in silico metabolic analysis can be an efficient way of developing strategies for strain improvement.

scholarly journals Cultivation at high osmotic pressure confers ubiquinone 8–independent protection of respiration on Escherichia coli

2019 ◽  
Vol 295 (4) ◽  
pp. 981-993 ◽  
Author(s):  
Laura Tempelhagen ◽  
Anita Ayer ◽  
Doreen E. Culham ◽  
Roland Stocker ◽  
Janet M. Wood
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Escherichia Coli ◽  
Electron Transfer ◽  
Oxygen Uptake ◽  
Osmotic Pressure ◽  
Respiratory Chain ◽  
Membrane Lipid ◽  
E Coli ◽  
Uptake Rates

Ubiquinone 8 (coenzyme Q8 or Q8) mediates electron transfer within the aerobic respiratory chain, mitigates oxidative stress, and contributes to gene expression in Escherichia coli. In addition, Q8 was proposed to confer bacterial osmotolerance by accumulating during growth at high osmotic pressure and altering membrane stability. The osmolyte trehalose and membrane lipid cardiolipin accumulate in E. coli cells cultivated at high osmotic pressure. Here, Q8 deficiency impaired E. coli growth at low osmotic pressure and rendered growth osmotically sensitive. The Q8 deficiency impeded cellular O2 uptake and also inhibited the activities of two proton symporters, the osmosensing transporter ProP and the lactose transporter LacY. Q8 supplementation decreased membrane fluidity in liposomes, but did not affect ProP activity in proteoliposomes, which is respiration-independent. Liposomes and proteoliposomes prepared with E. coli lipids were used for these experiments. Similar oxygen uptake rates were observed for bacteria cultivated at low and high osmotic pressures. In contrast, respiration was dramatically inhibited when bacteria grown at the same low osmotic pressure were shifted to high osmotic pressure. Thus, respiration was restored during prolonged growth of E. coli at high osmotic pressure. Of note, bacteria cultivated at low and high osmotic pressures had similar Q8 concentrations. The protection of respiration was neither diminished by cardiolipin deficiency nor conferred by trehalose overproduction during growth at low osmotic pressure, but rather might be achieved by Q8-independent respiratory chain remodeling. We conclude that osmotolerance is conferred through Q8-independent protection of respiration, not by altering physical properties of the membrane.

scholarly journals Rapid Growth of UropathogenicEscherichia coliduring Human Urinary Tract Infection

mBio ◽  
2018 ◽  
Vol 9 (2) ◽  
Author(s):  
Valerie S. Forsyth ◽  
Chelsie E. Armbruster ◽  
Sara N. Smith ◽  
Ali Pirani ◽  
A. Cody Springman ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Growth Rate ◽  
Urinary Tract ◽  
Growth Rates ◽  
High Growth ◽  
Replication Forks ◽  
Chromosomal Replication ◽  
E Coli ◽  
Tract Infections

ABSTRACTUropathogenicEscherichia coli(UPEC) strains cause most uncomplicated urinary tract infections (UTIs). These strains are a subgroup of extraintestinal pathogenicE. coli(ExPEC) strains that infect extraintestinal sites, including urinary tract, meninges, bloodstream, lungs, and surgical sites. Here, we hypothesize that UPEC isolates adapt to and grow more rapidly within the urinary tract than otherE. coliisolates and survive in that niche. To date, there has not been a reliable method available to measure their growth ratein vivo. Here we used two methods: segregation of nonreplicating plasmid pGTR902, and peak-to-trough ratio (PTR), a sequencing-based method that enumerates bacterial chromosomal replication forks present during cell division. In the murine model of UTI, UPEC strain growth was robustin vivo, matching or exceedingin vitrogrowth rates and only slowing after reaching high CFU counts at 24 and 30 h postinoculation (hpi). In contrast, asymptomatic bacteriuria (ABU) strains tended to maintain high growth ratesin vivoat 6, 24, and 30 hpi, and population densities did not increase, suggesting that host responses or elimination limited population growth. Fecal strains displayed moderate growth rates at 6 hpi but did not survive to later times. By PTR,E. coliin urine of human patients with UTIs displayed extraordinarily rapid growth during active infection, with a mean doubling time of 22.4 min. Thus, in addition to traditional virulence determinants, including adhesins, toxins, iron acquisition, and motility, very high growth ratesin vivoand resistance to the innate immune response appear to be critical phenotypes of UPEC strains.IMPORTANCEUropathogenicEscherichia coli(UPEC) strains cause most urinary tract infections in otherwise healthy women. While we understand numerous virulence factors are utilized byE. colito colonize and persist within the urinary tract, these properties are inconsequential unless bacteria can divide rapidly and survive the host immune response. To determine the contribution of growth rate to successful colonization and persistence, we employed two methods: one involving the segregation of a nonreplicating plasmid in bacteria as they divide and the peak-to-trough ratio, a sequencing-based method that enumerates chromosomal replication forks present during cell division. We found that UPEC strains divide extraordinarily rapidly during human UTIs. These techniques will be broadly applicable to measurein vivogrowth rates of other bacterial pathogens during host colonization.

scholarly journals Adaptation in a Mouse Colony Monoassociated with Escherichia coli K-12 for More than 1,000 Days

2010 ◽  
Vol 76 (14) ◽  
pp. 4655-4663 ◽  
Author(s):  
Sean M. Lee ◽  
Aaron Wyse ◽  
Aaron Lesher ◽  
Mary Lou Everett ◽  
Linda Lou ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Growth Rates ◽  
Bacterial Species ◽  
Intestinal Flora ◽  
Average Density ◽  
Host Bacterium ◽  
E Coli ◽  
K 12

ABSTRACT Although mice associated with a single bacterial species have been used to provide a simple model for analysis of host-bacteria relationships, bacteria have been shown to display adaptability when grown in a variety of novel environments. In this study, changes associated with the host-bacterium relationship in mice monoassociated with Escherichia coli K-12 over a period of 1,031 days were evaluated. After 80 days, phenotypic diversification of E. coli was observed, with the colonizing bacteria having a broader distribution of growth rates in the laboratory than the parent E. coli. After 1,031 days, which included three generations of mice and an estimated 20,000 generations of E. coli, the initially homogeneous bacteria colonizing the mice had evolved to have widely different growth rates on agar, a potential decrease in tendency for spontaneous lysis in vivo, and an increased tendency for spontaneous lysis in vitro. Importantly, mice at the end of the experiment were colonized at an average density of bacteria that was more than 3-fold greater than mice colonized on day 80. Evaluation of selected isolates on day 1,031 revealed unique restriction endonuclease patterns and differences between isolates in expression of more than 10% of the proteins identified by two-dimensional electrophoresis, suggesting complex changes underlying the evolution of diversity during the experiment. These results suggest that monoassociated mice might be used as a tool for characterizing niches occupied by the intestinal flora and potentially as a method of targeting the evolution of bacteria for applications in biotechnology.

scholarly journals A fourth Escherichia coli gene system with the potential to evolve beta-glucoside utilization.

Genetics ◽  
1988 ◽  
Vol 119 (3) ◽  
pp. 485-490
Author(s):  
L L Parker ◽  
B G Hall
Keyword(s):  
Escherichia Coli ◽  
Liquid Medium ◽  
Adaptive Evolution ◽  
Minimal Medium ◽  
Artificial Substrate ◽  
Second Step ◽  
Wild Type ◽  
E Coli ◽  
Gene System ◽  
Single Organism

Abstract Escherichia coli K12 is being used to study the potential for adaptive evolution that is present in the genome of a single organism. Wild-type E. coli K12 do not utilize any of the beta-glucoside sugars arbutin, salicin or cellobiose. It has been shown that mutations at three cryptic loci allow utilization of these sugars. Mutations in the bgl operon allow inducible growth on arbutin and salicin while cel mutations allow constitutive utilization of cellobiose as well as arbutin and salicin. Mutations in a third cryptic locus, arbT, allow the transport of arbutin. A salicin+ arbutin+ cellobiose+ mutant has been isolated from a strain which is deleted for the both the bgl and cel operons. Because the mutant utilized salicin and cellobiose as well as arbutin, it is unlikely it is the result of a mutation in arbT. A second step mutant exhibited enhanced growth on salicin and a third step mutant showed better growth on cellobiose. A fourfold level of induction in response to arbutin and a twofold level of induction in response to salicin was observed when these mutants were assayed on the artificial substrate p-nitrophenyl-beta-D-glucoside. Although growth on cellobiose minimal medium can be detected after prolonged periods of time, these strains are severely inhibited by cellobiose in liquid medium. This system has been cloned and does not hybridize to either bgl or cel specific probes. We have designated this gene system the sac locus. The sac locus is a fourth set of genes with the potential for evolving to provide beta-glucoside utilization.

scholarly journals In Silico Design for Systems-Based Metabolic Engineering In Escherichia Coli for The Bioconversion of Aerobic Glycerol to Succinic Acid

2020 ◽  
Author(s):  
Albert Enrique Tafur Rangel ◽  
Wendy Lorena Rios Guzman ◽  
Carmen Elvira Ojeda Cuella ◽  
Daissy Esther Mejia Perez ◽  
Ross Carlson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Succinic Acid ◽  
In Silico ◽  
Rational Design ◽  
Industrial Biotechnology ◽  
E Coli ◽  
Cell Factories ◽  
Transcriptomics Data

Abstract BackgroundGlycerol has become an interesting carbon source for industrial processes as consequence of the biodiesel business growth since it has shown promising results in terms of biomass/substrate yields. Selecting the appropriate metabolic targets to build efficient cell factories and maximize the desired chemical production in as little time as possible is a major challenge in industrial biotechnology. The engineering of microbial metabolism following rational design has been widely studied. However, it is a cost-, time-, and laborious-intensive process because of the cell network complexity; thus, to be proficient is needed known in advance the effects of gene deletions.ResultsAn in silico experiment was performed to model and understand the effects of metabolic engineering over the metabolism by transcriptomics data integration. In this study, systems-based metabolic engineering to predict the metabolic engineering targets was used in order to increase the bioconversion of glycerol to succinic acid by Escherichia coli. Transcriptomics analysis suggest insights of how increase the glycerol utilization of the cell for further design efficient cell factories. Three models were used; an E. coli core model, a model obtained after the integration of transcriptomics data obtained from E. coli growing in an optimized culture media, and a third one obtained after integration of transcriptomics data obtained from E. coli after adaptive laboratory evolution experiments. A total of 2402 strains were obtained from these three models. Fumarase and pyruvate dehydrogenase were frequently predicted in all the models, suggesting that these reactions are essential to increasing succinic acid production from glycerol. Finally, using flux balance analysis results for all the mutants predicted, a machine learning method was developed to predict new mutants as well as to propose optimal metabolic engineering targets and mutants based on the measurement of importance of each knockout’s (feature’s) contribution.ConclusionsThe combination of transcriptome, systems metabolic modeling, and machine learning analyses revealed versatile molecular mechanisms involved in the utilization of glycerol. These data provide a platform to improve the prediction of metabolic engineering targets to design efficient cell factories. Our results may also work a guide platform for the selection/engineering of microorganisms for production of interesting chemical compounds.

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