Dissecting the genetic and metabolic mechanisms of adaptation to the knockout of a major metabolic enzyme in Escherichia coli

Significance Understanding how microbes adapt to changing conditions is fundamental to biological science and engineering. For example, adaptation is a key driver of antimicrobial resistance, and adaptive laboratory evolution has become a key tool in biotechnology. Here, we present a comprehensive genetic and fluxomic analysis of 10 adaptively evolved Escherichia coli phosphoglucose isomerase (pgi) knockout strains. The loss of PGI, a key enzyme in glycolysis, results in massive redirection of carbon catabolic flux and reduction in growth rate. Adaptive evolution results in a 3.6-fold increase in growth rate, enabled by key mutations and metabolic flux rewiring. These include global transcriptional regulators, cofactor transhydrogenases, and the phosphotransferase system component crr. Overcoming key bottlenecks, rather than a broad metabolic response, is the dominant mechanism of adaptation. Unraveling the mechanisms of microbial adaptive evolution following genetic or environmental challenges is of fundamental interest in biological science and engineering. When the challenge is the loss of a metabolic enzyme, adaptive responses can also shed significant insight into metabolic robustness, regulation, and areas of kinetic limitation. In this study, whole-genome sequencing and high-resolution 13C-metabolic flux analysis were performed on 10 adaptively evolved pgi knockouts of Escherichia coli. Pgi catalyzes the first reaction in glycolysis, and its loss results in major physiological and carbon catabolism pathway changes, including an 80% reduction in growth rate. Following adaptive laboratory evolution (ALE), the knockouts increase their growth rate by up to 3.6-fold. Through combined genomic–fluxomic analysis, we characterized the mutations and resulting metabolic fluxes that enabled this fitness recovery. Large increases in pyridine cofactor transhydrogenase flux, correcting imbalanced production of NADPH and NADH, were enabled by direct mutations to the transhydrogenase genes sthA and pntAB. The phosphotransferase system component crr was also found to be frequently mutated, which corresponded to elevated flux from pyruvate to phosphoenolpyruvate. The overall energy metabolism was found to be strikingly robust, and what have been previously described as latently activated Entner–Doudoroff and glyoxylate shunt pathways are shown here to represent no real increases in absolute flux relative to the wild type. These results indicate that the dominant mechanism of adaptation was to relieve the rate-limiting steps in cofactor metabolism and substrate uptake and to modulate global transcriptional regulation from stress response to catabolism.

[1]  Christian L. Barrett,et al.  Genome-scale reconstruction of the Lrp regulatory network in Escherichia coli , 2008, Proceedings of the National Academy of Sciences.

[2]  Adam M. Feist,et al.  Evolution of E. coli on [U-13C]Glucose Reveals a Negligible Isotopic Influence on Metabolism and Physiology , 2016, PloS one.

[3]  Bernhard Ø. Palsson,et al.  Adaptive Evolution of Escherichia coli K-12 MG1655 during Growth on a Nonnative Carbon Source, l-1,2-Propanediol , 2010, Applied and Environmental Microbiology.

[4]  Martin Dragosits,et al.  Adaptive laboratory evolution – principles and applications for biotechnology , 2013, Microbial Cell Factories.

[5]  U. Sauer,et al.  Metabolic flux response to phosphoglucose isomerase knock-out in Escherichia coli and impact of overexpression of the soluble transhydrogenase UdhA. , 2001, FEMS Microbiology Letters.

[6]  U. Sauer,et al.  The Soluble and Membrane-bound Transhydrogenases UdhA and PntAB Have Divergent Functions in NADPH Metabolism of Escherichia coli* , 2004, Journal of Biological Chemistry.

[7]  Christopher P. Long,et al.  Quantifying biomass composition by gas chromatography/mass spectrometry. , 2014, Analytical chemistry.

[8]  C. Maranas,et al.  Improving prediction fidelity of cellular metabolism with kinetic descriptions. , 2015, Current opinion in biotechnology.

[9]  Christopher P. Long,et al.  13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling. , 2016, Metabolic engineering.

[10]  Adam M. Feist,et al.  Increased production of L-serine in Escherichia coli through Adaptive Laboratory Evolution. , 2017, Metabolic engineering.

[11]  Tom M. Conrad,et al.  Whole-genome resequencing of Escherichia coli K-12 MG1655 undergoing short-term laboratory evolution in lactate minimal media reveals flexible selection of adaptive mutations , 2009, Genome Biology.

[12]  Uwe Sauer,et al.  Transhydrogenase Promotes the Robustness and Evolvability of E. coli Deficient in NADPH Production , 2015, PLoS genetics.

[13]  J. Deutscher,et al.  The Bacterial Phosphoenolpyruvate:Carbohydrate Phosphotransferase System: Regulation by Protein Phosphorylation and Phosphorylation-Dependent Protein-Protein Interactions , 2014, Microbiology and Molecular Reviews.

[14]  M. Antoniewicz,et al.  (13)C metabolic flux analysis of the extremely thermophilic, fast growing, xylose-utilizing Geobacillus strain LC300. , 2016, Metabolic engineering.

[15]  Nobuyoshi Ishii,et al.  13C‐metabolic flux analysis for batch culture of Escherichia coli and its pyk and pgi gene knockout mutants based on mass isotopomer distribution of intracellular metabolites , 2010, Biotechnology progress.

[16]  S. P. Cornelius,et al.  Dispensability of Escherichia coli’s latent pathways , 2011, Proceedings of the National Academy of Sciences.

[17]  Matthias Heinemann,et al.  Functioning of a metabolic flux sensor in Escherichia coli , 2012, Proceedings of the National Academy of Sciences.

[18]  Christopher P. Long,et al.  Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis. , 2017, Metabolic engineering.

[19]  Luis H. Reyes,et al.  Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli. , 2012, Metabolic engineering.

[20]  Christopher P. Long,et al.  Enzyme I facilitates reverse flux from pyruvate to phosphoenolpyruvate in Escherichia coli , 2017, Nature Communications.

[21]  Christopher P. Long,et al.  Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system. , 2016, Metabolic engineering.

[22]  Edward J. O'Brien,et al.  Use of Adaptive Laboratory Evolution To Discover Key Mutations Enabling Rapid Growth of Escherichia coli K-12 MG1655 on Glucose Minimal Medium , 2014, Applied and Environmental Microbiology.

[23]  Bernhard O Palsson,et al.  Latent Pathway Activation and Increased Pathway Capacity Enable Escherichia coli Adaptation to Loss of Key Metabolic Enzymes* , 2006, Journal of Biological Chemistry.

[24]  Chikara Furusawa,et al.  Investigating the effects of perturbations to pgi and eno gene expression on central carbon metabolism in Escherichia coli using 13 C metabolic flux analysis , 2012, Microbial Cell Factories.

[25]  Adam M. Feist,et al.  Laboratory Evolution to Alternating Substrate Environments Yields Distinct Phenotypic and Genetic Adaptive Strategies , 2017, Applied and Environmental Microbiology.

[26]  J. Reed,et al.  RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations , 2012, Genome Biology.

[27]  Bernhard Ø. Palsson,et al.  Genetic Basis of Growth Adaptation of Escherichia coli after Deletion of pgi, a Major Metabolic Gene , 2010, PLoS genetics.

[28]  K. Jensen The Escherichia coli K-12 "wild types" W3110 and MG1655 have an rph frameshift mutation that leads to pyrimidine starvation due to low pyrE expression levels , 1993, Journal of bacteriology.

[29]  Christopher P. Long,et al.  Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli. , 2015, Metabolic engineering.

[30]  Christopher P. Long,et al.  Characterization of physiological responses to 22 gene knockouts in Escherichia coli central carbon metabolism. , 2016, Metabolic engineering.

[31]  C. Francke,et al.  How Phosphotransferase System-Related Protein Phosphorylation Regulates Carbohydrate Metabolism in Bacteria , 2006, Microbiology and Molecular Biology Reviews.

[32]  G. Bennett,et al.  Metabolic engineering and transhydrogenase effects on NADPH availability in escherichia coli , 2013, Biotechnology progress (Print).

[33]  Jeffrey E. Barrick,et al.  Genome evolution and adaptation in a long-term experiment with Escherichia coli , 2009, Nature.

[34]  M. Antoniewicz,et al.  COMPLETE-MFA: complementary parallel labeling experiments technique for metabolic flux analysis. , 2013, Metabolic engineering.

[35]  Adam M. Feist,et al.  Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring. , 2017, Metabolic engineering.

[36]  U. Sauer,et al.  Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. , 2003, European journal of biochemistry.

[37]  Chrystala Constantinidou,et al.  Identification of the CRP regulon using in vitro and in vivo transcriptional profiling. , 2004, Nucleic acids research.

[38]  Stephen S Fong,et al.  Metabolic gene–deletion strains of Escherichia coli evolve to computationally predicted growth phenotypes , 2004, Nature Genetics.

[39]  Christopher P. Long,et al.  Metabolic flux analysis of Escherichia coli knockouts: lessons from the Keio collection and future outlook. , 2014, Current opinion in biotechnology.

[40]  Pao-Yang Chen,et al.  Evolution, genomic analysis, and reconstruction of isobutanol tolerance in Escherichia coli , 2010, Molecular systems biology.

[41]  M. Antoniewicz,et al.  Measuring the Composition and Stable-Isotope Labeling of Algal Biomass Carbohydrates via Gas Chromatography/Mass Spectrometry. , 2016, Analytical chemistry.

[42]  Naoaki Ono,et al.  Transcriptome analysis of parallel-evolved Escherichia coli strains under ethanol stress , 2010, BMC Genomics.

[43]  Adam M. Feist,et al.  Evolution of Escherichia coli to 42 °C and Subsequent Genetic Engineering Reveals Adaptive Mechanisms and Novel Mutations , 2014, Molecular biology and evolution.

[44]  Anu Raghunathan,et al.  Comparative genome sequencing of Escherichia coli allows observation of bacterial evolution on a laboratory timescale , 2006, Nature Genetics.

[45]  Michael J. Wiser,et al.  Long-Term Dynamics of Adaptation in Asexual Populations , 2013, Science.

[46]  Ali R. Zomorrodi,et al.  A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data. , 2014, Metabolic engineering.

[47]  F. Bolivar,et al.  Current knowledge of the Escherichia coli phosphoenolpyruvate–carbohydrate phosphotransferase system: peculiarities of regulation and impact on growth and product formation , 2012, Applied Microbiology and Biotechnology.

[48]  Pei Yee Ho,et al.  Multiple High-Throughput Analyses Monitor the Response of E. coli to Perturbations , 2007, Science.

[49]  Ke Chen,et al.  Global Rebalancing of Cellular Resources by Pleiotropic Point Mutations Illustrates a Multi-scale Mechanism of Adaptive Evolution. , 2016, Cell systems.

[50]  H. Mori,et al.  Responses of theCentral Metabolism in Escherichia coli to PhosphoglucoseIsomerase and Glucose-6-Phosphate DehydrogenaseKnockouts , 2003, Journal of bacteriology.

[51]  Jeffrey D. Orth,et al.  In silico method for modelling metabolism and gene product expression at genome scale , 2012, Nature Communications.