ECO-MP: E coli-Metabolic Pathway-development of Genome-scale Metabolic Pathway Database for Escherichia coli

A comparative whole genome analysis was performed on three newly sequenced Escherichia coli O157:H7 strains with different stx profiles, previously isolated from feedlot cattle [C1-010 (stx1−, stx2c+), C1-057 (stx−), and C1-067 (stx1+, stx2a+)], as well as five foodborne outbreak strains and six stx-negative strains from NCBI. Phylogenomic analysis demonstrated that the stx2c-carrying C1-010 and stx-negative C1-057 strains were grouped with the six NCBI stx-negative E. coli O157:H7 strains in Cluster 1, whereas the stx2a-carrying C1-067 and five foodborne outbreak strains were clustered together in Cluster 2. Based on different clusters, we selected the three newly sequenced strains, one stx2a-carrying strain, and the six NCBI stx-negative strains and identify their prophages at the stx insertion sites. All stx-carrying prophages contained both the three Red recombination genes (exo, bet, gam) and their repressor cI. On the other hand, the majority of the stx-negative prophages carried only the three Red recombination genes, but their repressor cI was absent. In the absence of the repressor cI, the consistent expression of the Red recombination genes in prophages might result in more frequent gene exchanges, potentially increasing the probability of the acquisition of stx genes. We further investigated each of the 10 selected E. coli O157:H7 strains for their respective unique metabolic pathway genes. Seven unique metabolic pathway genes in the two stx2a-carrying strains and one in the single stx2c-carrying and seven stx-negative strains were found to be associated with an upstream insertion sequence 629 within a conserved region among these strains. The presence of more unique metabolic pathway genes in stx2a-carrying E. coli O157:H7 strains may potentially increase their competitiveness in complex environments, such as feedlot cattle. For the stx2c-carrying and stx-negative E. coli O157:H7 strains, the fact that they were grouped into the same phylogenomic cluster and had the same unique metabolic pathway genes suggested that they may also share closely related evolutionary pathways. As a consequence, gene exchange between them is more likely to occur. Results from this study could potentially serve as a basis to help develop strategies to reduce the prevalence of pathogenic E. coli O157:H7 in livestock and downstream food production environments.

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Escherichia coli Increases its ATP Concentration in Weakly Acidic Environments Principally through the Glycolytic Pathway

Genes ◽

10.3390/genes11090991 ◽

2020 ◽

Vol 11 (9) ◽

pp. 991 ◽

Cited By ~ 1

Author(s):

Wenbin Zhang ◽

Xin Chen ◽

Wei Sun ◽

Tao Nie ◽

Natalie Quanquin ◽

...

Keyword(s):

Escherichia Coli ◽

Oxidative Phosphorylation ◽

Metabolic Pathway ◽

Acid Resistance ◽

Intestinal Bacteria ◽

Atp Production ◽

E Coli ◽

Major Producer ◽

Acidic Conditions ◽

Acidic Environments

Acid resistance is an intrinsic characteristic of intestinal bacteria in order to survive passage through the stomach. Adenosine triphosphate (ATP), the ubiquitous chemical used to power metabolic reactions, activate signaling cascades, and form precursors of nucleic acids, was also found to be associated with the survival of Escherichia coli (E. coli) in acidic environments. The metabolic pathway responsible for elevating the level of ATP inside these bacteria during acid adaptation has been unclear. E. coli uses several mechanisms of ATP production, including oxidative phosphorylation, glycolysis and the oxidation of organic compounds. To uncover which is primarily used during adaptation to acidic conditions, we broadly analyzed the levels of gene transcription of multiple E. coli metabolic pathway components. Our findings confirmed that the primary producers of ATP in E. coli undergoing mild acidic stress are the glycolytic enzymes Glk, PykF and Pgk, which are also essential for survival under markedly acidic conditions. By contrast, the transcription of genes related to oxidative phosphorylation was downregulated, despite it being the major producer of ATP in neutral pH environments.

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New insights into the adaptive transcriptional response to nitrogen starvation in Escherichia coli

Biochemical Society Transactions ◽

10.1042/bst20180502 ◽

2018 ◽

Vol 46 (6) ◽

pp. 1721-1728 ◽

Cited By ~ 6

Author(s):

Amy Switzer ◽

Daniel R. Brown ◽

Sivaramesh Wigneshweraraj

Keyword(s):

Escherichia Coli ◽

Adaptive Response ◽

Large Scale ◽

Nitrogen Starvation ◽

Transcriptional Response ◽

Adaptive Responses ◽

Nitrogenous Compounds ◽

E Coli ◽

N Starvation ◽

Genome Scale

Bacterial adaptive responses to biotic and abiotic stresses often involve large-scale reprogramming of the transcriptome. Since nitrogen is an essential component of the bacterial cell, the transcriptional basis of the adaptive response to nitrogen starvation has been well studied. The adaptive response to N starvation in Escherichia coli is primarily a ‘scavenging response’, which results in the transcription of genes required for the transport and catabolism of nitrogenous compounds. However, recent genome-scale studies have begun to uncover and expand some of the intricate regulatory complexities that underpin the adaptive transcriptional response to nitrogen starvation in E. coli. The purpose of this review is to highlight some of these new developments.

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

Journal of Bacteriology ◽

10.1128/jb.185.21.6392-6399.2003 ◽

2003 ◽

Vol 185 (21) ◽

pp. 6392-6399 ◽

Cited By ~ 53

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.

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Mutations that improve efficiency of a weak-link enzyme are rare compared to adaptive mutations elsewhere in the genome

eLife ◽

10.7554/elife.53535 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 3

Author(s):

Andrew B Morgenthaler ◽

Wallis R Kinney ◽

Christopher C Ebmeier ◽

Corinne M Walsh ◽

Daniel J Snyder ◽

...

Keyword(s):

Escherichia Coli ◽

Metabolic Pathway ◽

Weak Link ◽

Experimental Studies ◽

Wild Type ◽

Gene Encoding ◽

Evolutionary Trajectory ◽

Adaptive Mutations ◽

E Coli ◽

Essential Function

New enzymes often evolve by gene amplification and divergence. Previous experimental studies have followed the evolutionary trajectory of an amplified gene, but have not considered mutations elsewhere in the genome when fitness is limited by an evolving gene. We have evolved a strain of Escherichia coli in which a secondary promiscuous activity has been recruited to serve an essential function. The gene encoding the ‘weak-link’ enzyme amplified in all eight populations, but mutations improving the newly needed activity occurred in only one. Most adaptive mutations occurred elsewhere in the genome. Some mutations increase expression of the enzyme upstream of the weak-link enzyme, pushing material through the dysfunctional metabolic pathway. Others enhance production of a co-substrate for a downstream enzyme, thereby pulling material through the pathway. Most of these latter mutations are detrimental in wild-type E. coli, and thus would require reversion or compensation once a sufficient new activity has evolved.

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

Journal of Bacteriology ◽

10.1128/jb.185.21.6400-6408.2003 ◽

2003 ◽

Vol 185 (21) ◽

pp. 6400-6408 ◽

Cited By ~ 80

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.

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Metabolic Engineering of Carotenoid Biosynthesis in Escherichia coli by Ordered Gene Assembly in Bacillus subtilis

Applied and Environmental Microbiology ◽

10.1128/aem.02268-06 ◽

2006 ◽

Vol 73 (4) ◽

pp. 1355-1361 ◽

Cited By ~ 84

Author(s):

Tomoko Nishizaki ◽

Kenji Tsuge ◽

Mitsuhiro Itaya ◽

Nobuhide Doi ◽

Hiroshi Yanagawa

Keyword(s):

Escherichia Coli ◽

Bacillus Subtilis ◽

Metabolic Engineering ◽

Metabolic Pathway ◽

Dry Weight ◽

Carotenoid Biosynthesis ◽

Gene Assembly ◽

Biosynthetic Genes ◽

E Coli ◽

Foreign Genes

ABSTRACT We attempted to optimize the production of zeaxanthin in Escherichia coli by reordering five biosynthetic genes in the natural carotenoid cluster of Pantoea ananatis. Newly designed operons for zeaxanthin production were constructed by the ordered gene assembly in Bacillus subtilis (OGAB) method, which can assemble multiple genes in one step using an intrinsic B. subtilis plasmid transformation system. The highest level of production of zeaxanthin in E. coli (820 μg/g [dry weight]) was observed in the transformant with a plasmid in which the gene order corresponds to the order of the zeaxanthin metabolic pathway (crtE-crtB-crtI-crtY-crtZ), among a series of plasmids with circularly permuted gene orders. Although two of five operons using intrinsic zeaxanthin promoters failed to assemble in B. subtilis, the full set of operons was obtained by repressing operon expression during OGAB assembly with a p R promoter-cI repressor system. This result suggests that repressing the expression of foreign genes in B. subtilis is important for their assembly by the OGAB method. For all tested operons, the abundance of mRNA decreased monotonically with the increasing distance of the gene from the promoter in E. coli, and this may influence the yield of zeaxanthin. Our results suggest that rearrangement of biosynthetic genes in the order of the metabolic pathway by the OGAB method could be a useful approach for metabolic engineering.

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Genome-Scale Metabolic Models and Machine Learning Reveal Genetic Determinants of Antibiotic Resistance in Escherichia coli and Unravel the Underlying Metabolic Adaptation Mechanisms

mSystems ◽

10.1128/msystems.00913-20 ◽

2021 ◽

Author(s):

Nicole Pearcy ◽

Yue Hu ◽

Michelle Baker ◽

Alexandre Maciel-Guerra ◽

Ning Xue ◽

...

Keyword(s):

Machine Learning ◽

Escherichia Coli ◽

Antibiotic Resistance ◽

Health Concern ◽

Metabolic Adaptation ◽

Genetic Determinants ◽

Content Type ◽

E Coli ◽

Adaptation Mechanisms ◽

Genome Scale

Escherichia coli is a major public health concern given its increasing level of antibiotic resistance worldwide and extraordinary capacity to acquire and spread resistance via horizontal gene transfer with surrounding species and via mutations in its existing genome. E. coli also exhibits a large amount of metabolic pathway redundancy, which promotes resistance via metabolic adaptability. In this study, we developed a computational approach that integrates machine learning with metabolic modeling to understand the correlation between AMR and metabolic adaptation mechanisms in this model bacterium.

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Model Driven Analysis of the Biosynthesis of 1,4-butanediol from Renewable Feedstocks in Escherichia coli

Revista de Chimie ◽

10.37358/rc.70.19.11.7651 ◽

2019 ◽

Vol 70 (11) ◽

pp. 3808-3817

Author(s):

Zsolt Bodor ◽

Szabolcs Lanyi ◽

Beata Albert ◽

Katalin Bodor ◽

Aurelia Cristina Nechifor ◽

...

Keyword(s):

Escherichia Coli ◽

Metabolic Model ◽

E Coli ◽

Model Driven ◽

Metabolic Characteristics ◽

Strain Design ◽

Renewable Feedstocks ◽

Coa Ligase ◽

Coa Transferase ◽

Genome Scale

Bio-based, environmentally benign production of commodity chemicals such as 1,4-butanediol (BDO) from renewable feedstocks is highly challenging due to the lack of natural synthesis pathways. Herein, we present a systematic model-driven evaluation of the production potential for Escherichia coli to produce BDO from renewable carbohydrates (glucose, glycerol). Computational analysis was carried out in order to decipher the metabolic characteristics under various genetic and environmental conditions. Optimal strain designs were achieved using only two (adhE2- alcohol dehydrogenase and cat/sucCD- 4-hydroxybutyrate-CoA transferase/4-hydroxybutyryl-CoA ligase) heterologous reactions; highest yields were attained for: glucose ~0.37 g g-1 (3 knockouts, anaerobically) and glycerol ~0.43 g g-1 (4 knockouts, microaerobically). The maximum achievable production yield was over 95% of the theoretical maximum potential for glucose and over 75% for glycerol. In regards to the genome-scale metabolic model predictions, a metabolically engineered E. coli was created to analyze the new biosynthetic pathway stability and functionality. Considering the preliminary outcomes the strain and pathway is stable under fermentative conditions and a limited quantity of BDO ~1 mg L-1 was obtained, therefore long-term adaptive evolution is mandatory. This study outlines a strain design and analysis pipeline -systems biology-based approach- for non-native compounds production strains.

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Molecular and Functional Insights into the Regulation of D-Galactonate Metabolism by the Transcriptional Regulator DgoR inEscherichia coli

Journal of Bacteriology ◽

10.1128/jb.00281-18 ◽

2018 ◽

Vol 201 (4) ◽

Cited By ~ 1

Author(s):

Bhupinder Singh ◽

Garima Arya ◽

Neeladrita Kundu ◽

Akshay Sangwan ◽

Shachikanta Nongthombam ◽

...

Keyword(s):

Escherichia Coli ◽

Dna Binding ◽

Metabolic Pathway ◽

Transcriptional Regulator ◽

Inverted Repeats ◽

Missense Mutations ◽

Content Type ◽

E Coli ◽

K 12 ◽

Gntr Family

ABSTRACTd-Galactonate, an aldonic sugar acid, is used as a carbon source byEscherichia coli, and the structuraldgogenes involved in its metabolism have previously been investigated. Here, using genetic, biochemical and bioinformatics approaches, we present the first detailed molecular and functional insights into the regulation ofd-galactonate metabolism inE. coliK-12 by the transcriptional regulator DgoR. We found thatdgoRdeletion accelerates the growth ofE. coliind-galactonate concomitant with the strong constitutive expression ofdgogenes. In thedgolocus, sequence upstream ofdgoRalone harbors thed-galactonate-inducible promoter that likely drives the expression of alldgogenes. DgoR exerts repression on thedgooperon by binding two inverted repeats overlapping thedgopromoter. Binding ofd-galactonate induces a conformational change in DgoR to derepress thedgooperon. The findings from our work firmly place DgoR in the GntR family of transcriptional regulators: DgoR binds an operator sequence [5′-TTGTA(G/C)TACA(A/T)-3′] matching the signature of GntR family members that recognize inverted repeats [5′-(N)yGT(N)xAC(N)y-3′, wherexandyindicate the number of nucleotides, which varies], and it shares critical protein-DNA contacts. We also identified features in DgoR that are otherwise less conserved in the GntR family. Recently, missense mutations indgoRwere recovered in a naturalE. coliisolate adapted to the mammalian gut. Our results show these mutants to be DNA binding defective, emphasizing that mutations in thedgo-regulatory elements are selected in the host to allow simultaneous induction ofdgogenes. The present study sets the basis to explore the regulation ofdgogenes in additional enterobacterial strains where they have been implicated in host-bacterium interactions.IMPORTANCEd-Galactonate is a widely prevalent aldonic sugar acid. Despite the proposed significance of thed-galactonate metabolic pathway in the interaction of enteric bacteria with their hosts, there are no details on its regulation even inEscherichia coli, which has been known to utilized-galactonate since the 1970s. Here, using multiple methodologies, we identified the promoter, operator, and effector of DgoR, the transcriptional repressor ofd-galactonate metabolism inE. coli. We establish DgoR as a GntR family transcriptional regulator. Recently, a human urinary tract isolate ofE. coliintroduced in the mouse gut was found to accumulate missense mutations indgoR. Our results show these mutants to be DNA binding defective, hence emphasizing the role of thed-galactonate metabolic pathway in bacterial colonization of the mammalian gut.

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