Evolution of gene knockout strains of E. coli reveal regulatory architectures governed by metabolism

Nature Communications

Volumn 9, Issue 1, 2018, Pages

  McCloskey, Douglas ^a,b   Xu, Sibei ^a   Sandberg, Troy E ^a   Brunk, Elizabeth ^a   Hefner, Ying ^a   Szubin, Richard ^a   Feist, Adam M ^a,b   Palsson, Bernhard O ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Chalmers University of Technology   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTATION; COLIFORM BACTERIUM; EVOLUTION; GENE; GENE EXPRESSION; METABOLISM; METABOLITE; MUTATION;

ADAPTATION; ARTICLE; BACTERIAL METABOLISM; BACTERIAL MUTATION; BACTERIAL STRAIN; BIOMICS; CONTROLLED STUDY; ESCHERICHIA COLI K 12; GENE KNOCKOUT; METABOLITE; MOLECULAR EVOLUTION; NONHUMAN; GENE REGULATORY NETWORK; GENETICS; METABOLISM; MUTATION; PHENOTYPE; PHYSIOLOGY;

ESCHERICHIA COLI K12;

ESCHERICHIA COLI K12; EVOLUTION, MOLECULAR; GENE KNOCKOUT TECHNIQUES; GENE REGULATORY NETWORKS; METABOLIC NETWORKS AND PATHWAYS; MUTATION; PHENOTYPE;

EID: 85053463527     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/s41467-018-06219-9     Document Type: Article

References (115)

1. Ishii, N. et al. Multiple high-throughput analyses monitor the response of E. coli to perturbations. Science 316, 593–597 (2007)
2. Fuhrer, T., Zampieri, M., Sévin, D. C., Sauer, U. & Zamboni, N. Genomewide landscape of gene-metabolome associations in Escherichia coli. Mol. Syst. Biol. 13, 907 (2017)
3. Haverkorn van Rijsewijk, B. R. B., Nanchen, A., Nallet, S., Kleijn, R. J. & Sauer, U. Large-scale 13C-flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli. Mol. Syst. Biol. 7, 477 (2011)
4. Long, C. P., Gonzalez, J. E., Sandoval, N. R. & Antoniewicz, M. R. Characterization of physiological responses to 22 gene knockouts in Escherichia coli central carbon metabolism. Metab. Eng. 37, 102–113 (2016)
5. Baba, T. et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, 2006.0008 (2006)
6. Giaever, G. et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391 (2002)
7. de Berardinis, V. et al. A complete collection of single-gene deletion mutants of Acinetobacter baylyi ADP1. Mol. Syst. Biol. 4, 174 (2008)
8. Porwollik, S. et al. Defined single-gene and multi-gene deletion mutant collections in Salmonella enterica sv Typhimurium. PLoS ONE 9, e99820 (2014)
9. Nakahigashi, K. et al. Systematic phenome analysis of Escherichia coli multiple-knockout mutants reveals hidden reactions in central carbon metabolism. Mol. Syst. Biol. 5, 306 (2009)
10. Tenaillon, O. et al. Tempo and mode of genome evolution in a 50,000-generation experiment. Nature 536, 165–170 (2016)
11. Plucain, J. et al. Epistasis and allele specificity in the emergence of a stable polymorphism in Escherichia coli. Science 343, 1366–1369 (2014)
12. Dragosits, M. & Mattanovich, D. Adaptive laboratory evolution—principles and applications for biotechnology. Microb. Cell Fact. 12, 64 (2013)
13. Carroll, S. M. & Marx, C. J. Evolution after introduction of a novel metabolic pathway consistently leads to restoration of wild-type physiology. PLoS Genet. 9, e1003427 (2013)
14. Charusanti, P. et al. Genetic basis of growth adaptation of Escherichia coli after deletion of pgi, a major metabolic gene. PLoS Genet. 6, e1001186 (2010)
15. Cooper, T. F., Rozen, D. E. & Lenski, R. E. Parallel changes in gene expression after 20,000 generations of evolution in Escherichia coli. Proc. Natl Acad. Sci. USA 100, 1072–1077 (2003)
16. Cooper, T. F., Remold, S. K., Lenski, R. E. & Schneider, D. Expression profiles reveal parallel evolution of epistatic interactions involving the CRP regulon in Escherichia coli. PLoS Genet. 4, e35 (2008)
17. Gresham, D. et al. The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet. 4, e1000303 (2008)
18. McDonald, M. J., Gehrig, S. M., Meintjes, P. L., Zhang, X.-X. & Rainey, P. B. Adaptive divergence in experimental populations of Pseudomonas fluorescens. IV. Genetic constraints guide evolutionary trajectories in a parallel adaptive radiation. Genetics 183, 1041–1053 (2009)
19. Kvitek, D. J. & Sherlock, G. Reciprocal sign epistasis between frequently experimentally evolved adaptive mutations causes a rugged fitness landscape. PLoS Genet. 7, e1002056 (2011)
20. Toprak, E. et al. Evolutionary paths to antibiotic resistance under dynamically sustained drug selection. Nat. Genet. 44, 101–105 (2011)
21. Lenski, R. E. et al. Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli. Proc. Biol. Sci. 282, 2292–2301 (2015)
22. Moore, F. B., Rozen, D. E. & Lenski, R. E. Pervasive compensatory adaptation in Escherichia coli. Proc. Biol. Sci. 267, 515–522 (2000)
23. Szamecz, B. et al. The genomic landscape of compensatory evolution. PLoS Biol. 12, e1001935 (2014)
24. Blank, D., Wolf, L., Ackermann, M. & Silander, O. K. The predictability of molecular evolution during functional innovation. Proc. Natl Acad. Sci. USA 111, 3044–3049 (2014)
25. Rancati, G. et al. Aneuploidy underlies rapid adaptive evolution of yeast cells deprived of a conserved cytokinesis motor. Cell 135, 879–893 (2008)
26. Taylor, T. B. et al. Evolution. Evolutionary resurrection of flagellar motility via rewiring of the nitrogen regulation system. Science 347, 1014–1017 (2015)
27. McCloskey, D. et al. Adaptive laboratory evolution resolves energy depletion to maintain high aromatic metabolite phenotypes in Escherichia coli strains lacking the phosphotransferase system. Metab. Eng. 48, 233–242 (2018)
28. McCloskey, D. et al. Adaptation to the coupling of glycolysis to toxic methylglyoxal production in tpiA deletion strains of Escherichia coli requires synchronized and counterintuitive genetic changes. Metab. Eng. 48, 82–93 (2018)
29. McCloskey, D. et al. Multiple optimal phenotypes overcome redox and glycolytic intermediate metabolite imbalances in Escherichia coli pgi knockout evolutions. Appl Environ Microbiol. AEM.00823-18 (2018)
30. McCloskey, D. et al. Growth adaptation of gnd and sdhCB Escherichia coli deletion strains diverges from a similar initial perturbation of the transcriptome. Front Microbiol. 9, 1793 (2018)
31. LaCroix, R. A. et al. Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium. Appl. Environ. Microbiol. 81, 17–30 (2015)
32. Sandberg, T. E. et al. Evolution of Escherichia coli to 42 °C and subsequent genetic engineering reveals adaptive mechanisms and novel mutations. Mol. Biol. Evol. 31, 2647–2662 (2014)
33. McCloskey, D., Utrilla, J., Naviaux, R. K., Palsson, B. O. & Feist, A. M. Fast Swinnex filtration (FSF): a fast and robust sampling and extraction method suitable for metabolomics analysis of cultures grown in complex media. Metabolomics 11, 198–209 (2014)
34. McCloskey, D., Gangoiti, J. A., Palsson, B. O. & Feist, A. M. A pH and solvent optimized reverse-phase ion-paring-LC–MS/MS method that leverages multiple scan-types for targeted absolute quantification of intracellular metabolites. Metabolomics 11, 1338–1350 (2015)
35. McCloskey, D., Young, J. D., Xu, S., Palsson, B. O. & Feist, A. M. MID max: LC-MS/MS method for measuring the precursor and product mass isotopomer distributions of metabolic intermediates and cofactors for metabolic flux analysis applications. Anal. Chem. 88, 1362–1370 (2016)
36. McCloskey, D., Young, J. D., Xu, S., Palsson, B. O. & Feist, A. M. Modeling method for increased precision and scope of directly measurable fluxes at a genome-scale. Anal. Chem. 88, 3844–3852 (2016)
37. Conrad, T. M., Lewis, N. E. & Palsson, B. Ø. Microbial laboratory evolution in the era of genome-scale science. Mol. Syst. Biol. 7, 509 (2011)
38. Kochanowski, K. et al. Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli. Mol. Syst. Biol. 13, 903 (2017)
39. Kochanowski, K. et al. Functioning of a metabolic flux sensor in Escherichia coli. Proc. Natl Acad. Sci. USA 110, 1130–1135 (2013)
40. Nelson, D. L. & Cox, M. M. Lehninger Principles of Biochemistry (W.H. Freeman, New York, 2013)
41. Gama-Castro, S. et al. RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond. Nucleic Acids Res. 44, D133–D143 (2016)
42. Cho, S. et al. The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli. Nucleic Acids Res. 43, 3079–3088 (2015)
43. Federowicz, S. et al. Determining the control circuitry of redox metabolism at the genome-scale. PLoS Genet. 10, e1004264 (2014)
44. Kim, D. et al. Comparative analysis of regulatory elements between Escherichia coli and Klebsiella pneumoniae by genome-wide transcription start site profiling. PLoS Genet. 8, e1002867 (2012)
45. Cho, B.-K., Federowicz, S., Park, Y.-S., Zengler, K. & Palsson, B. Ø. Deciphering the transcriptional regulatory logic of amino acid metabolism. Nat. Chem. Biol. 8, 65–71 (2011)
46. Martínez-Antonio, A. & Collado-Vides, J. Identifying global regulators in transcriptional regulatory networks in bacteria. Curr. Opin. Microbiol. 6, 482–489 (2003)
47. Utrilla, J. et al. Global rebalancing of cellular resources by pleiotropic point mutations illustrates a multi-scale mechanism of adaptive evolution. Cell Syst. 2, 260–271 (2016)
48. Gunasekara, S. M. et al. Directed evolution of the Escherichia coli cAMP receptor protein at the cAMP pocket. J. Biol. Chem. 290, 26587–26596 (2015)
49. Alvarez, A. F. & Georgellis, D. In vitro and in vivo analysis of the ArcB/A redox signaling pathway. Methods Enzymol. 471, 205–228 (2010)
50. Meng, L. M., Kilstrup, M. & Nygaard, P. Autoregulation of PurR repressor synthesis and involvement of purR in the regulation of purB, purC, purL, purMN and guaBA expression in Escherichia coli. Eur. J. Biochem. 187, 373–379 (1990)
51. He, B., Shiau, A., Choi, K. Y., Zalkin, H. & Smith, J. M. Genes of the Escherichia coli pur regulon are negatively controlled by a repressor-operator interaction. J. Bacteriol. 172, 4555–4562 (1990)
52. Cho, B.-K. et al. The PurR regulon in Escherichia coli K-12 MG1655. Nucleic Acids Res. 39, 6456–6464 (2011)
53. Pittard, J., Camakaris, H. & Yang, J. The TyrR regulon. Mol. Microbiol. 55, 16–26 (2005)
54. Wallace, B. J. & Pittard, J. Regulator gene controlling enzymes concerned in tyrosine biosynthesis in Escherichia coli. J. Bacteriol. 97, 1234–1241 (1969)
55. Vanderpool, C. K. & Gottesman, S. Involvement of a novel transcriptional activator and small RNA in post-transcriptional regulation of the glucose phosphoenolpyruvate phosphotransferase system. Mol. Microbiol. 54, 1076–1089 (2004)
56. Vanderpool, C. K. & Gottesman, S. The novel transcription factor SgrR coordinates the response to glucose-phosphate stress. J. Bacteriol. 189, 2238–2248 (2007)
57. Richards, G. R., Patel, M. V., Lloyd, C. R. & Vanderpool, C. K. Depletion of glycolytic intermediates plays a key role in glucose-phosphate stress in Escherichia coli. J. Bacteriol. 195, 4816–4825 (2013)
58. Hackett, S. R. et al. Systems-level analysis of mechanisms regulating yeast metabolic flux. Science 354, 432–449 (2016)
59. Daran-Lapujade, P. et al. The fluxes through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscriptional levels. Proc. Natl Acad. Sci. USA 104, 15753–15758 (2007)
60. Covert, M. W., Knight, E. M., Reed, J. L., Herrgard, M. J. & Palsson, B. O. Integrating high-throughput and computational data elucidates bacterial networks. Nature 429, 92–96 (2004)
61. Vital-Lopez, F. G., Wallqvist, A. & Reifman, J. Bridging the gap between gene expression and metabolic phenotype via kinetic models. BMC Syst. Biol. 7, 63 (2013)
62. Koussounadis, A., Langdon, S. P., Um, I. H., Harrison, D. J. & Smith, V. A. Relationship between differentially expressed mRNA and mRNA-protein correlations in a xenograft model system. Sci. Rep. 5, 10775 (2015)
63. Maier, T., Güell, M. & Serrano, L. Correlation of mRNA and protein in complex biological samples. FEBS Lett. 583, 3966–3973 (2009)
64. Cho, B.-K., Knight, E. M., Barrett, C. L. & Palsson, B. Ø. Genome-wide analysis of Fis binding in Escherichia coli indicates a causative role for A-/AT-tracts. Genome Res. 18, 900–910 (2008)
65. Bradley, M. D., Beach, M. B., de Koning, A. P. J., Pratt, T. S. & Osuna, R. Effects of Fis on Escherichia coli gene expression during different growth stages. Microbiology 153, 2922–2940 (2007)
66. Weinstein-Fischer, D. & Altuvia, S. Differential regulation of Escherichia coli topoisomerase I by Fis. Mol. Microbiol. 63, 1131–1144 (2007)
67. Bobrovskyy, M. & Vanderpool, C. K. Diverse mechanisms of post-transcriptional repression by the small RNA regulator of glucose-phosphate stress. Mol. Microbiol. 99, 254–273 (2016)
68. Sun, Y. & Vanderpool, C. K. Physiological consequences of multiple-target regulation by the small RNA SgrS in Escherichia coli. J. Bacteriol. 195, 4804–4815 (2013)
69. Charpentier, B. & Branlant, C. The Escherichia coli gapA gene is transcribed by the vegetative RNA polymerase holoenzyme E sigma 70 and by the heat shock RNA polymerase E sigma 32. J. Bacteriol. 176, 830–839 (1994)
70. Thouvenot, B., Charpentier, B. & Branlant, C. The strong efficiency of the Escherichia coli gapA P1 promoter depends on a complex combination of functional determinants. Biochem. J. 383, 371–382 (2004)
71. Kim, D. et al. Systems assessment of transcriptional regulation on central carbon metabolism by Cra and CRP. bioRxiv 080929. 10.1101/080929 (2016)
72. Muse, W. B. & Bender, R. A. The nac (nitrogen assimilation control) gene from Escherichia coli. J. Bacteriol. 180, 1166–1173 (1998)
73. Huerta, A. M. & Collado-Vides, J. Sigma70 promoters in Escherichia coli: specific transcription in dense regions of overlapping promoter-like signals. J. Mol. Biol. 333, 261–278 (2003)
74. Levin, H. L. & Schachman, H. K. Regulation of aspartate transcarbamoylase synthesis in Escherichia coli: analysis of deletion mutations in the promoter region of the pyrBI operon. Proc. Natl Acad. Sci. USA 82, 4643–4647 (1985)
75. Jensen, K. F. Hyper-regulation of pyr gene expression in Escherichia coli cells with slow ribosomes. Evidence for RNA polymerase pausing in vivo? Eur. J. Biochem. 175, 587–593 (1988)
76. Chen, Z. et al. Discovery of Fur binding site clusters in Escherichia coli by information theory models. Nucleic Acids Res. 35, 6762–6777 (2007)
77. Méhi, O. et al. Perturbation of iron homeostasis promotes the evolution of antibiotic resistance. Mol. Biol. Evol. 31, 2793–2804 (2014)
78. Beauchene, N. A. et al. Impact of anaerobiosis on expression of the iron-responsive fur and RyhB regulons. mBio 6, e01947–15 (2015)
79. Lavrrar, J. L., Christoffersen, C. A. & McIntosh, M. A. Fur-DNA interactions at the bidirectional fepDGC-entS promoter region in Escherichia coli. J. Mol. Biol. 322, 983–995 (2002)
80. González Barrios, A. F. et al. Autoinducer 2 controls biofilm formation in Escherichia coli through a novel motility quorum-sensing regulator (MqsR, B3022). J. Bacteriol. 188, 305–316 (2006)
81. Seo, S. W., Kim, D., Szubin, R. & Palsson, B. O. Genome-wide reconstruction of OxyR and SoxRS transcriptional regulatory networks under oxidative stress in Escherichia coli K-12 MG1655. Cell Rep. 12, 1289–1299 (2015)
82. Tramonti, A., De Canio, M. & De Biase, D. GadX/GadW-dependent regulation of the Escherichia coli acid fitness island: transcriptional control at the gadY-gadW divergent promoters and identification of four novel 42 bp GadX/GadW-specific binding sites. Mol. Microbiol. 70, 965–982 (2008)
83. Seo, S. W., Kim, D., O’Brien, E. J., Szubin, R. & Palsson, B. O. Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli. Nat. Commun. 6, 7970 (2015)
84. Majdalani, N. & Gottesman, S. The Rcs phosphorelay: a complex signal transduction system. Annu. Rev. Microbiol. 59, 379–405 (2005)
85. Torres-Cabassa, A. S. & Gottesman, S. Capsule synthesis in Escherichia coli K-12 is regulated by proteolysis. J. Bacteriol. 169, 981–989 (1987)
86. Datsenko, K. A. & Wanner, B. L. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl Acad. Sci. USA 97, 6640–6645 (2000)
87. Sambrook, J. & Russell, D. W. Molecular Cloning: A Laboratory Manual. 3rd edn (Cold Spring-Harbour Laboratory Press, Cold Spring-Harbour, 2001)
88. Fong, S. S. et al. In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Biotechnol. Bioeng. 91, 643–648 (2005)
89. Orth, J. D. et al. A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011. Mol. Syst. Biol. 7, 535 (2011)
90. Schellenberger, J. & Palsson, B. Ø. Use of randomized sampling for analysis of metabolic networks. J. Biol. Chem. 284, 5457–5461 (2009)
91. McCloskey, D. et al. A model-driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K-12 MG1655 that is biochemically and thermodynamically consistent. Biotechnol. Bioeng. 111, 803–815 (2014)
92. Honaker, J., King, G. & Blackwell, M. Amelia II: a program for missing data. J. Stat. Softw. 45, 1–47 (2011)
93. Rocke, D., Tillinghast, J., Durbin-Johnson, B. & Wu, S. L. LMGene software for data transformation and identification of differentially expressed genes in gene expression arrays. R package version 2.4. 0
94. Young, J. D. INCA: a computational platform for isotopically non-stationary metabolic flux analysis. Bioinformatics 30, 1333–1335 (2014)
95. Megchelenbrink, W., Huynen, M. & Marchiori, E. optGpSampler: An improved tool for uniformly sampling the solution-space of genome-scale metabolic networks. PLoS ONE 9, e86587 (2014)
96. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Bowtie: an ultrafast memory-efficient short read aligner. Genome Biol. 10, R25 (2009)
97. Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010)
98. Deatherage, D. E. & Barrick, J. E. Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq. Methods Mol. Biol. 1151, 165–188 (2014)
99. Berman, H. M. et al. The Protein Data Bank. Nucleic Acids Res. 28, 235–242 (2000)
100. Berman, H., Henrick, K. & Nakamura, H. Announcing the worldwide Protein Data Bank. Nat. Struct. Biol. 10, 980 (2003)
101. Xu, D. & Zhang, Y. Ab Initio structure prediction for Escherichia coli: towards genome-wide protein structure modeling and fold assignment. Sci. Rep. 3, 1895 (2013)
102. Wu, S., Skolnick, J. & Zhang, Y. Ab initio modeling of small proteins by iterative TASSER simulations. BMC Biol. 5, 17 (2007)
103. Keseler, I. M. et al. EcoCyc: fusing model organism databases with systems biology. Nucleic Acids Res. 41, D605–D612 (2013)
104. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996). 27–8
105. Stacklies, W., Redestig, H., Scholz, M., Walther, D. & Selbig, J. pcaMethods—a bioconductor package providing PCA methods for incomplete data. Bioinformatics 23, 1164–1167 (2007)
106. Mevik, B. H. & Wehrens, R. The pls package: principal component and partial least squares regression in R. J. Stat. Softw. 18, 1–23 (2007)
107. Alexa, A. & Rahnenfuhrer, J. topGO: enrichment analysis for gene ontology. R package version 2 (2010)
108. Carlson, M. G. O. db: A set of annotation maps describing the entire. Gene Ontology. 2013. R package version 3 (2013)
109. Grossmann, S., Bauer, S., Robinson, P. N. & Vingron, M. Improved detection of overrepresentation of Gene-Ontology annotations with parent–child analysis. Bioinformatics 23, 3024–3031 (2007)
110. Hastings, J. et al. The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013. Nucleic Acids Res. 41, D456–D463 (2013)
111. Moretti, S. et al. MetaNetX/MNXref—reconciliation of metabolites and biochemical reactions to bring together genome-scale metabolic networks. Nucleic Acids Res. 44, D523–D526 (2016)
112. Ganter, M., Bernard, T., Moretti, S., Stelling, J. & Pagni, M. MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks. Bioinformatics 29, 815–816 (2013)
113. Bernard, T. et al. Reconciliation of metabolites and biochemical reactions for metabolic networks. Brief. Bioinformatics 15, 123–135 (2014)
114. Marks, G. T., Susler, M. & Harrison, D. H. T. Mutagenic studies on histidine 98 of methylglyoxal synthase: effects on mechanism and conformational change. Biochemistry 43, 3802–3813 (2004)
115. Saadat, D. & Harrison, D. H. Mirroring perfection: the structure of methylglyoxal synthase complexed with the competitive inhibitor 2-phosphoglycolate. Biochemistry 39, 2950–2960 (2000)