Addition of Escherichia coli K-12 Growth Observation and Gene Essentiality Data to the EcoCyc Database

Mackie, Amanda; Paley, Suzanne M.; Keseler, Ingrid M.; Shearer, Alexander G.; Paulsen, Ian T.; Karp, Peter D.

doi:10.1128/jb.01209-13

Cited by 10 publications

(10 citation statements)

References 18 publications

(7 reference statements)

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“… E. coli has the remarkable ability to use many carbon sources for growth which makes it possible to exhaustively probe central metabolism pathways using different carbon sources. Since methodologies differ from lab to lab, unifying different gene essentiality data sets has been difficult ( 33 ). This speaks to the need for more comprehensive data sets that explore a large number of conditions using the same strains and methodology.…”

Section: Introductionmentioning

confidence: 99%

Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

Tong

French

Zahed

et al. 2020

mBio

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Central metabolism is a topic that has been studied for decades, and yet, this process is still not fully understood in Escherichia coli, perhaps the most amenable and well-studied model organism in biology. To further our understanding, we used a high-throughput method to measure the growth kinetics of each of 3,796 E. coli single-gene deletion mutants in 30 different carbon sources. In total, there were 342 genes (9.01%) encompassing a breadth of biological functions that showed a growth phenotype on at least 1 carbon source, demonstrating that carbon metabolism is closely linked to a large number of processes in the cell. We identified 74 genes that showed low growth in 90% of conditions, defining a set of genes which are essential in nutrient-limited media, regardless of the carbon source. The data are compiled into a Web application, Carbon Phenotype Explorer (CarPE), to facilitate easy visualization of growth curves for each mutant strain in each carbon source. Our experimental data matched closely with the predictions from the EcoCyc metabolic model which uses flux balance analysis to predict growth phenotypes. From our comparisons to the model, we found that, unexpectedly, phosphoenolpyruvate carboxylase (ppc) was required for robust growth in most carbon sources other than most trichloroacetic acid (TCA) cycle intermediates. We also identified 51 poorly annotated genes that showed a low growth phenotype in at least 1 carbon source, which allowed us to form hypotheses about the functions of these genes. From this list, we further characterized the ydhC gene and demonstrated its role in adenosine efflux. IMPORTANCE While there has been much study of bacterial gene dispensability, there is a lack of comprehensive genome-scale examinations of the impact of gene deletion on growth in different carbon sources. In this context, a lot can be learned from such experiments in the model microbe Escherichia coli where much is already understood and there are existing tools for the investigation of carbon metabolism and physiology (1). Gene deletion studies have practical potential in the field of antibiotic drug discovery where there is emerging interest in bacterial central metabolism as a target for new antibiotics (2). Furthermore, some carbon utilization pathways have been shown to be critical for initiating and maintaining infection for certain pathogens and sites of infection (3–5). Here, with the use of high-throughput solid medium phenotyping methods, we have generated kinetic growth measurements for 3,796 genes under 30 different carbon source conditions. This data set provides a foundation for research that will improve our understanding of genes with unknown function, aid in predicting potential antibiotic targets, validate and advance metabolic models, and help to develop our understanding of E. coli metabolism.

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Section: Introductionmentioning

confidence: 99%

Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

Tong

French

Zahed

et al. 2020

mBio

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“…We observed that a loss of bacterial viability proportional to mutagenic potency beyond a mutation rate of ∼4 × 10 −7 substitutions per bp per generation, corresponding to an average of ∼1.9 substitutions per genome per generation. Given that ∼10–30% of the E. coli genome has been estimated to be essential 26 , this mutation rate threshold corresponds to ∼0.2–0.6 mutations in an essential gene/generation.…”

Section: Resultsmentioning

confidence: 99%

Development of potent in vivo mutagenesis plasmids with broad mutational spectra

2015

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Methods to enhance random mutagenesis in cells offer advantages over in vitro mutagenesis, but current in vivo methods suffer from a lack of control, genomic instability, low efficiency and narrow mutational spectra. Using a mechanism-driven approach, we created a potent, inducible, broad-spectrum and vector-based mutagenesis system in E. coli that enhances mutation 322,000-fold over basal levels, surpassing the mutational efficiency and spectra of widely used in vivo and in vitro methods. We demonstrate that this system can be used to evolve antibiotic resistance in wild-type E. coli in <24 h, outperforming chemical mutagens, ultraviolet light and the mutator strain XL1-Red under similar conditions. This system also enables the continuous evolution of T7 RNA polymerase variants capable of initiating transcription using the T3 promoter in <10 h. Our findings enable broad-spectrum mutagenesis of chromosomes, episomes and viruses in vivo, and are applicable to both bacterial and bacteriophage-mediated laboratory evolution platforms.

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“…Another factor contributing to the large number of food molecules are environmental adaptations of E. coli . As recently summarized by Mackie et al [ 42 ] E. coli can grow under different conditions, for example, under aerobic and anaerobic conditions, or using different carbon sources. The extended food set allows for all of these alternative pathways to be functioning within the RAF network.…”

Section: Resultsmentioning

confidence: 99%

“…A second food set was created based on the laboratory conditions given for E. coli growth on glucose-6-phosphate and glucose as in [ 42 ]. The reactions included in the resulting RAF network were mapped to E. coli Kegg pathways [ 43 ].…”

Section: Methodsmentioning

confidence: 99%

Autocatalytic sets in E. coli metabolism

Sousa

Hordijk²,

Steel

et al. 2015

J Syst Chem

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Background: A central unsolved problem in early evolution concerns self-organization towards higher complexity in chemical reaction networks. In theory, autocatalytic sets have useful properties to help model such transitions. Autocatalytic sets are chemical reaction systems in which molecules belonging to the set catalyze the synthesis of other members of the set. Given an external supply of starting molecules -the food set -and the conditions that (i) all reactions are catalyzed by at least one molecule, and (ii) each molecule can be constructed from the food set by a sequence of reactions, the system becomes a reflexively autocatalytic food-generated network (RAF set). Autocatalytic networks and RAFs have been studied extensively as mathematical models for understanding the properties and parameters that influence self-organizational tendencies. However, despite their appeal, the relevance of RAFs for real biochemical networks that exist in nature has, so far, remained virtually unexplored. Results: Here we investigate the best-studied metabolic network, that of Escherichia coli, for the existence of RAFs. We find that the largest RAF encompasses almost the entire E. coli cytosolic reaction network. We systematically study its structure by considering the impact of removing catalysts or reactions. We show that, without biological knowledge, finding the minimum food set that maintains a given RAF is NP-complete. We apply a randomized algorithm to find (approximately) smallest subsets of the food set that suffice to sustain the original RAF. Conclusions: The existence of RAF sets within a microbial metabolic network indicates that RAFs capture properties germane to biological organization at the level of single cells. Moreover, the interdependency between the different metabolic modules, especially concerning cofactor biosynthesis, points to the important role of spontaneous (non-enzymatic) reactions in the context of early evolution.

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Addition of Escherichia coli K-12 Growth Observation and Gene Essentiality Data to the EcoCyc Database

Cited by 10 publications

References 18 publications

Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

Development of potent in vivo mutagenesis plasmids with broad mutational spectra

Autocatalytic sets in E. coli metabolism

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