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Title: Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow

Abstract

Understanding the complex interactions of protein posttranslational modifications (PTMs) represents a major challenge in metabolic engineering, synthetic biology, and the biomedical sciences. In this work, we present a workflow that integrates multiplex automated genome editing (MAGE), genome-scale metabolic modeling, and atomistic molecular dynamics to study the effects of PTMs on metabolic enzymes and microbial fitness. This workflow incorporates complementary approaches across scientific disciplines; provides molecular insight into how PTMs influence cellular fitness during nutrient shifts; and demonstrates how mechanistic details of PTMs can be explored at different biological scales. As a proof of concept, we present a global analysis of PTMs on enzymes in the metabolic network of Escherichia coli. Based on our workflow results, we conduct a more detailed, mechanistic analysis of the PTMs in three proteins: enolase, serine hydroxymethyltransferase, and transaldolase. Finally, application of this workflow identified the roles of specific PTMs in observed experimental phenomena and demonstrated how individual PTMs regulate enzymes, pathways, and, ultimately, cell phenotypes.

Authors:
ORCiD logo [1];  [2];  [3];  [1]; ORCiD logo [1];  [4];  [5]; ORCiD logo [6];  [7];  [3];  [8];  [9];  [1]
+ Show Author Affiliations
  1. University of California, San Diego, La Jolla, CA (United States)
  2. Harvard Medical School, Boston, MA (United States); University of California, San Diego, La Jolla, CA (United States)
  3. Chinese Academy of Sciences, Shanghai (China)
  4. University of California, San Diego, La Jolla, CA (United States); Kyung Hee Univ., Yongin (Korea)
  5. Brigham Young Univ., Provo, UT (United States)
  6. Columbia University Medical Center, New York, NY (United States); Harvard Medical School, Boston, MA (United States)
  7. Korea Advanced Institute of Science and Technology, Daejeon (Korea)
  8. University of California, San Diego, La Jolla, CA (United States); Technical Univ. of Denmark, Lyngby (Denmark)
  9. Harvard Medical School, Boston, MA (United States)
Publication Date:
Research Org.:
Harvard Medical School, Boston, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Contributing Org.:
National Energy Research Scientific Computing Center and XSEDE computer facilities (MCB140152)
OSTI Identifier:
1528919
Grant/Contract Number:  
FG02-02ER63445
Resource Type:
Accepted Manuscript
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 115; Journal Issue: 43; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Escherichia coli; metabolic modeling; flux balance analysis; post-translational modification; multiplex automated genome engineering; molecular dynamics

Citation Formats

Brunk, Elizabeth, Chang, Roger L., Xia, Jing, Hefzi, Hooman, Yurkovich, James T., Kim, Donghyuk, Buckmiller, Evan, Wang, Harris H., Cho, Byung-Kwan, Yang, Chen, Palsson, Bernhard O., Church, George M., and Lewis, Nathan E. Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow. United States: N. p., 2018. Web. doi:10.1073/pnas.1811971115.
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Brunk, Elizabeth, Chang, Roger L., Xia, Jing, Hefzi, Hooman, Yurkovich, James T., Kim, Donghyuk, Buckmiller, Evan, Wang, Harris H., Cho, Byung-Kwan, Yang, Chen, Palsson, Bernhard O., Church, George M., & Lewis, Nathan E. Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow. United States. https://doi.org/10.1073/pnas.1811971115
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Brunk, Elizabeth, Chang, Roger L., Xia, Jing, Hefzi, Hooman, Yurkovich, James T., Kim, Donghyuk, Buckmiller, Evan, Wang, Harris H., Cho, Byung-Kwan, Yang, Chen, Palsson, Bernhard O., Church, George M., and Lewis, Nathan E. Tue . "Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow". United States. https://doi.org/10.1073/pnas.1811971115. https://www.osti.gov/servlets/purl/1528919.
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@article{osti_1528919,
title = {Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow},
author = {Brunk, Elizabeth and Chang, Roger L. and Xia, Jing and Hefzi, Hooman and Yurkovich, James T. and Kim, Donghyuk and Buckmiller, Evan and Wang, Harris H. and Cho, Byung-Kwan and Yang, Chen and Palsson, Bernhard O. and Church, George M. and Lewis, Nathan E.},
abstractNote = {Understanding the complex interactions of protein posttranslational modifications (PTMs) represents a major challenge in metabolic engineering, synthetic biology, and the biomedical sciences. In this work, we present a workflow that integrates multiplex automated genome editing (MAGE), genome-scale metabolic modeling, and atomistic molecular dynamics to study the effects of PTMs on metabolic enzymes and microbial fitness. This workflow incorporates complementary approaches across scientific disciplines; provides molecular insight into how PTMs influence cellular fitness during nutrient shifts; and demonstrates how mechanistic details of PTMs can be explored at different biological scales. As a proof of concept, we present a global analysis of PTMs on enzymes in the metabolic network of Escherichia coli. Based on our workflow results, we conduct a more detailed, mechanistic analysis of the PTMs in three proteins: enolase, serine hydroxymethyltransferase, and transaldolase. Finally, application of this workflow identified the roles of specific PTMs in observed experimental phenomena and demonstrated how individual PTMs regulate enzymes, pathways, and, ultimately, cell phenotypes.},
doi = {10.1073/pnas.1811971115},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 43,
volume = 115,
place = {United States},
year = {Tue Oct 09 00:00:00 EDT 2018},
month = {Tue Oct 09 00:00:00 EDT 2018}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1073/pnas.1811971115
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Cited by: 27 works
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Figures / Tables:

Fig. 1 Fig. 1: A workflow for bridging systems and molecular science with multiomics data, genome-scale models of E. coli metabolism, and MD simulations. Our workflow involves a staging of computational and experimental methods: (1) computational genome-scale modeling to predict which enzymes require regulation across specific nutrient shifts; (2) genome editing throughmore » MAGE to probe the effect of changing PTM sites on cellular fitness; and (3) MD and in vitro enzyme assays to probe the effect of modifying a residue that is a known PTM site on protein configuration.« less
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Works referenced in this record:

GEEQBOX : A MATLAB Toolbox for Generalized Estimating Equations and Quasi-Least Squares
journal, January 2008

  • Ratcliffe, Sarah J.; Shults, Justine
  • Journal of Statistical Software, Vol. 25, Issue 14
  • DOI: 10.18637/jss.v025.i14

Robustness in Glyoxylate Bypass Regulation
journal, March 2009

EcoCyc: a comprehensive database resource for Escherichia coli
journal, December 2004

  • Keseler, Ingrid M.; Collado-Vides, Julio; Gama-Castro, Socorro
  • Nucleic Acids Research, Vol. 33, Issue suppl_1, p. D334-D337
  • DOI: 10.1093/nar/gki108

Regulation of Isocitrate Dehydrogenase Activity in Escherichia coli on Adaptation to Acetate
journal, January 1971

Phosphoproteome Analysis of E. coli Reveals Evolutionary Conservation of Bacterial Ser/Thr/Tyr Phosphorylation
journal, October 2007

Post-translational modifications as key regulators of bacterial metabolic fluxes
journal, April 2015

  • Pisithkul, Tippapha; Patel, Nishaben M.; Amador-Noguez, Daniel
  • Current Opinion in Microbiology, Vol. 24
  • DOI: 10.1016/j.mib.2014.12.006

The Escherichia coli Phosphotyrosine Proteome Relates to Core Pathways and Virulence
journal, June 2013

On the Future of Genomic Data
journal, February 2011

Steinernema glaseri surface enolase: Molecular cloning, biological characterization, and role in host immune suppression
journal, October 2012

Computational solutions for omics data
journal, April 2013

  • Berger, Bonnie; Peng, Jian; Singh, Mona
  • Nature Reviews Genetics, Vol. 14, Issue 5
  • DOI: 10.1038/nrg3433

Lysine Acetylation Is a Highly Abundant and Evolutionarily Conserved Modification in Escherichia Coli
journal, August 2008

Global dynamics of Escherichia coli phosphoproteome in central carbon metabolism under changing culture conditions
journal, August 2015

The crystal structure and identification of NQM1/YGR043C, a transaldolase from Saccharomyces cerevisiae
journal, September 2008

  • Huang, Hua; Rong, Hui; Li, Xu
  • Proteins: Structure, Function, and Bioinformatics, Vol. 73, Issue 4
  • DOI: 10.1002/prot.22237

High-Throughput Proteomics
journal, June 2014

Programming cells by multiplex genome engineering and accelerated evolution
journal, July 2009

  • Wang, Harris H.; Isaacs, Farren J.; Carr, Peter A.
  • Nature, Vol. 460, Issue 7257, p. 894-898
  • DOI: 10.1038/nature08187

Posttranslational regulation of microbial metabolism
journal, October 2015

Identification of lysine succinylation as a new post-translational modification
journal, December 2010

  • Zhang, Zhihong; Tan, Minjia; Xie, Zhongyu
  • Nature Chemical Biology, Vol. 7, Issue 1
  • DOI: 10.1038/nchembio.495

Use of Randomized Sampling for Analysis of Metabolic Networks
journal, October 2008

  • Schellenberger, Jan; Palsson, Bernhard Ø.
  • Journal of Biological Chemistry, Vol. 284, Issue 9
  • DOI: 10.1074/jbc.R800048200

Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald
journal, August 2013

  • Salomon-Ferrer, Romelia; Götz, Andreas W.; Poole, Duncan
  • Journal of Chemical Theory and Computation, Vol. 9, Issue 9
  • DOI: 10.1021/ct400314y

RNA Structural Determinants of Optimal Codons Revealed by MAGE-Seq
journal, December 2016

Riding the wave of biological data
journal, March 2011

AMBER force-field parameters for phosphorylated amino acids in different protonation states: phosphoserine, phosphothreonine, phosphotyrosine, and phosphohistidine
journal, October 2005

  • Homeyer, Nadine; Horn, Anselm H. C.; Lanig, Harald
  • Journal of Molecular Modeling, Vol. 12, Issue 3
  • DOI: 10.1007/s00894-005-0028-4

High-throughput discovery metabolomics
journal, February 2015

Stoichiometry of Site-specific Lysine Acetylation in an Entire Proteome
journal, June 2014

  • Baeza, Josue; Dowell, James A.; Smallegan, Michael J.
  • Journal of Biological Chemistry, Vol. 289, Issue 31
  • DOI: 10.1074/jbc.M114.581843

Coordination of microbial metabolism
journal, March 2014

  • Chubukov, Victor; Gerosa, Luca; Kochanowski, Karl
  • Nature Reviews Microbiology, Vol. 12, Issue 5
  • DOI: 10.1038/nrmicro3238

Twisted Schiff base intermediates and substrate locale revise transaldolase mechanism
journal, August 2011

  • Lehwess-Litzmann, Anja; Neumann, Piotr; Parthier, Christoph
  • Nature Chemical Biology, Vol. 7, Issue 10
  • DOI: 10.1038/nchembio.633

Encoding human serine phosphopeptides in bacteria for proteome-wide identification of phosphorylation-dependent interactions
journal, June 2018

  • Barber, Karl W.; Muir, Paul; Szeligowski, Richard V.
  • Nature Biotechnology, Vol. 36, Issue 7
  • DOI: 10.1038/nbt.4150

Sequencing technologies — the next generation
journal, December 2009

  • Metzker, Michael L.
  • Nature Reviews Genetics, Vol. 11, Issue 1
  • DOI: 10.1038/nrg2626

Beyond gene expression: The impact of protein post-translational modifications in bacteria
journal, January 2014

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
journal, August 2011

  • Schellenberger, Jan; Que, Richard; Fleming, Ronan M. T.
  • Nature Protocols, Vol. 6, Issue 9
  • DOI: 10.1038/nprot.2011.308

Genomes by design
journal, August 2015

  • Haimovich, Adrian D.; Muir, Paul; Isaacs, Farren J.
  • Nature Reviews Genetics, Vol. 16, Issue 9
  • DOI: 10.1038/nrg3956

Comparison of multiple Amber force fields and development of improved protein backbone parameters
journal, November 2006

  • Hornak, Viktor; Abel, Robert; Okur, Asim
  • Proteins: Structure, Function, and Bioinformatics, Vol. 65, Issue 3
  • DOI: 10.1002/prot.21123

Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation
journal, August 2008

  • López-Maury, Luis; Marguerat, Samuel; Bähler, Jürg
  • Nature Reviews Genetics, Vol. 9, Issue 8
  • DOI: 10.1038/nrg2398

Genome-scale promoter engineering by coselection MAGE
journal, April 2012

  • Wang, Harris H.; Kim, Hwangbeom; Cong, Le
  • Nature Methods, Vol. 9, Issue 6, p. 591-593
  • DOI: 10.1038/nmeth.1971

What is flux balance analysis?
journal, March 2010

  • Orth, Jeffrey D.; Thiele, Ines; Palsson, Bernhard Ø
  • Nature Biotechnology, Vol. 28, Issue 3
  • DOI: 10.1038/nbt.1614

Constraint-based models predict metabolic and associated cellular functions
journal, January 2014

  • Bordbar, Aarash; Monk, Jonathan M.; King, Zachary A.
  • Nature Reviews Genetics, Vol. 15, Issue 2
  • DOI: 10.1038/nrg3643

Ancient Regulatory Role of Lysine Acetylation in Central Metabolism
journal, November 2017

  • Nakayasu, Ernesto S.; Burnet, Meagan C.; Walukiewicz, Hanna E.
  • mBio, Vol. 8, Issue 6
  • DOI: 10.1128/mBio.01894-17

Acetyl-Phosphate Is a Critical Determinant of Lysine Acetylation in E. coli
journal, July 2013

Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods
journal, February 2012

  • Lewis, Nathan E.; Nagarajan, Harish; Palsson, Bernhard O.
  • Nature Reviews Microbiology, Vol. 10, Issue 4
  • DOI: 10.1038/nrmicro2737
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    Works referencing / citing this record:

    Protein post-translational modifications in bacteria
    journal, September 2019

    • Macek, Boris; Forchhammer, Karl; Hardouin, Julie
    • Nature Reviews Microbiology, Vol. 17, Issue 11
    • DOI: 10.1038/s41579-019-0243-0

    Global Lysine Acetylation in Escherichia coli Results from Growth Conditions That Favor Acetate Fermentation
    journal, February 2019

    • Schilling, Birgit; Basisty, Nathan; Christensen, David G.
    • Journal of Bacteriology, Vol. 201, Issue 9
    • DOI: 10.1128/jb.00768-18

    The Impact of ackA, pta, and ackA-pta Mutations on Growth, Gene Expression and Protein Acetylation in Escherichia coli K-12
    journal, February 2020

    • Schütze, Andrea; Benndorf, Dirk; Püttker, Sebastian
    • Frontiers in Microbiology, Vol. 11
    • DOI: 10.3389/fmicb.2020.00233
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