Principles of proteome allocation are revealed using proteomic data and genome-scale models
Abstract
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.
- Authors:
-
- Univ. of California, San Diego, La Jolla, CA (United States)
- Stanford Univ., Stanford, CA (United States)
- Univ. of California, San Diego, La Jolla, CA (United States); The Technical Univ. of Denmark, Horsholm (Denmark)
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1373286
- Grant/Contract Number:
- SC0008701
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Scientific Reports
- Additional Journal Information:
- Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 2045-2322
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 60 APPLIED LIFE SCIENCES; biochemical networks; computer modelling
Citation Formats
Yang, Laurence, Yurkovich, James T., Lloyd, Colton J., Ebrahim, Ali, Saunders, Michael A., and Palsson, Bernhard O. Principles of proteome allocation are revealed using proteomic data and genome-scale models. United States: N. p., 2016.
Web. doi:10.1038/srep36734.
Yang, Laurence, Yurkovich, James T., Lloyd, Colton J., Ebrahim, Ali, Saunders, Michael A., & Palsson, Bernhard O. Principles of proteome allocation are revealed using proteomic data and genome-scale models. United States. https://doi.org/10.1038/srep36734
Yang, Laurence, Yurkovich, James T., Lloyd, Colton J., Ebrahim, Ali, Saunders, Michael A., and Palsson, Bernhard O. Fri .
"Principles of proteome allocation are revealed using proteomic data and genome-scale models". United States. https://doi.org/10.1038/srep36734. https://www.osti.gov/servlets/purl/1373286.
@article{osti_1373286,
title = {Principles of proteome allocation are revealed using proteomic data and genome-scale models},
author = {Yang, Laurence and Yurkovich, James T. and Lloyd, Colton J. and Ebrahim, Ali and Saunders, Michael A. and Palsson, Bernhard O.},
abstractNote = {Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.},
doi = {10.1038/srep36734},
journal = {Scientific Reports},
number = 1,
volume = 6,
place = {United States},
year = {Fri Nov 18 00:00:00 EST 2016},
month = {Fri Nov 18 00:00:00 EST 2016}
}
Free Publicly Available Full Text
Publisher's Version of Record
Other availability
Search WorldCat to find libraries that may hold this journal
Cited by: 21 works
Citation information provided by
Web of Science
Web of Science
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Expanded microbial genome coverage and improved protein family annotation in the COG database
journal, November 2014
- Galperin, Michael Y.; Makarova, Kira S.; Wolf, Yuri I.
- Nucleic Acids Research, Vol. 43, Issue D1
Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli
journal, August 2015
- Seo, Sang Woo; Kim, Donghyuk; O’Brien, Edward J.
- Nature Communications, Vol. 6, Issue 1
Reconstruction and modeling protein translocation and compartmentalization in Escherichia coli at the genome-scale
journal, September 2014
- Liu, Joanne K.; O’Brien, Edward J.; Lerman, Joshua A.
- BMC Systems Biology, Vol. 8, Issue 1
Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments
journal, June 2016
- O’Brien, Edward J.; Utrilla, Jose; Palsson, Bernhard O.
- PLOS Computational Biology, Vol. 12, Issue 6
Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
journal, February 2015
- Hui, Sheng; Silverman, Josh M.; Chen, Stephen S.
- Molecular Systems Biology, Vol. 11, Issue 2
Bacterial growth: global effects on gene expression, growth feedback and proteome partition
journal, August 2014
- Klumpp, Stefan; Hwa, Terence
- Current Opinion in Biotechnology, Vol. 28
Hierarchy of non-glucose sugars in Escherichia coli
journal, December 2014
- Aidelberg, Guy; Towbin, Benjamin D.; Rothschild, Daphna
- BMC Systems Biology, Vol. 8, Issue 1
Large‐scale 13 C‐flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli
journal, January 2011
- Haverkorn van Rijsewijk, Bart R. B.; Nanchen, Annik; Nallet, Sophie
- Molecular Systems Biology, Vol. 7, Issue 1
Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism
journal, April 2014
- Machado, Daniel; Herrgård, Markus
- PLoS Computational Biology, Vol. 10, Issue 4
Robust flux balance analysis of multiscale biochemical reaction networks
journal, July 2013
- Sun, Yuekai; Fleming, Ronan MT; Thiele, Ines
- BMC Bioinformatics, Vol. 14, Issue 1
Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS: Metabolic flux profiling in E.���coli
journal, March 2003
- Fischer, Eliane; Sauer, Uwe
- European Journal of Biochemistry, Vol. 270, Issue 5
Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli
journal, September 2014
- Seo, Sang Woo; Kim, Donghyuk; Latif, Haythem
- Nature Communications, Vol. 5, Issue 1
Multiscale Modeling of Metabolism and Macromolecular Synthesis in E. coli and Its Application to the Evolution of Codon Usage
journal, September 2012
- Thiele, Ines; Fleming, Ronan M. T.; Que, Richard
- PLoS ONE, Vol. 7, Issue 9
Condition-Dependent Cell Volume and Concentration of Escherichia coli to Facilitate Data Conversion for Systems Biology Modeling
journal, July 2011
- Volkmer, Benjamin; Heinemann, Matthias
- PLoS ONE, Vol. 6, Issue 7
Shrinking the Metabolic Solution Space Using Experimental Datasets
journal, August 2012
- Reed, Jennifer L.
- PLoS Computational Biology, Vol. 8, Issue 8
Use of Adaptive Laboratory Evolution To Discover Key Mutations Enabling Rapid Growth of Escherichia coli K-12 MG1655 on Glucose Minimal Medium
journal, October 2014
- LaCroix, Ryan A.; Sandberg, Troy E.; O'Brien, Edward J.
- Applied and Environmental Microbiology, Vol. 81, Issue 1
Genome-wide Reconstruction of OxyR and SoxRS Transcriptional Regulatory Networks under Oxidative Stress in Escherichia coli K-12 MG1655
journal, August 2015
- Seo, Sang Woo; Kim, Donghyuk; Szubin, Richard
- Cell Reports, Vol. 12, Issue 8
A Comparison of the Costs and Benefits of Bacterial Gene Expression
journal, October 2016
- Price, Morgan N.; Wetmore, Kelly M.; Deutschbauer, Adam M.
- PLOS ONE, Vol. 11, Issue 10
In silico method for modelling metabolism and gene product expression at genome scale
journal, January 2012
- Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem
- Nature Communications, Vol. 3, Issue 1
Optimizing genome-scale network reconstructions
journal, May 2014
- Monk, Jonathan; Nogales, Juan; Palsson, Bernhard O.
- Nature Biotechnology, Vol. 32, Issue 5
Global Transcriptional Programs Reveal a Carbon Source Foraging Strategy by Escherichia coli
journal, February 2005
- Liu, Mingzhu; Durfee, Tim; Cabrera, Julio E.
- Journal of Biological Chemistry, Vol. 280, Issue 16
Network-based prediction of human tissue-specific metabolism
journal, August 2008
- Shlomi, Tomer; Cabili, Moran N.; Herrgård, Markus J.
- Nature Biotechnology, Vol. 26, Issue 9
Global Rebalancing of Cellular Resources by Pleiotropic Point Mutations Illustrates a Multi-scale Mechanism of Adaptive Evolution
journal, April 2016
- Utrilla, Jose; O’Brien, Edward J.; Chen, Ke
- Cell Systems, Vol. 2, Issue 4
The quantitative and condition-dependent Escherichia coli proteome
journal, December 2015
- Schmidt, Alexander; Kochanowski, Karl; Vedelaar, Silke
- Nature Biotechnology, Vol. 34, Issue 1
Current knowledge of the Escherichia coli phosphoenolpyruvate–carbohydrate phosphotransferase system: peculiarities of regulation and impact on growth and product formation
journal, May 2012
- Escalante, Adelfo; Salinas Cervantes, Ania; Gosset, Guillermo
- Applied Microbiology and Biotechnology, Vol. 94, Issue 6
solveME: fast and reliable solution of nonlinear ME models
journal, September 2016
- Yang, Laurence; Ma, Ding; Ebrahim, Ali
- BMC Bioinformatics, Vol. 17, Issue 1
Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol
journal, May 2011
- Yim, Harry; Haselbeck, Robert; Niu, Wei
- Nature Chemical Biology, Vol. 7, Issue 7
Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
journal, November 2002
- Ibarra, Rafael U.; Edwards, Jeremy S.; Palsson, Bernhard O.
- Nature, Vol. 420, Issue 6912
Pseudo-transition Analysis Identifies the Key Regulators of Dynamic Metabolic Adaptations from Steady-State Data
journal, October 2015
- Gerosa, Luca; Haverkorn van Rijsewijk, Bart R. B.; Christodoulou, Dimitris
- Cell Systems, Vol. 1, Issue 4
Methods for integration of transcriptomic data in genome-scale metabolic models
journal, August 2014
- Kim, Min Kyung; Lun, Desmond S.
- Computational and Structural Biotechnology Journal, Vol. 11, Issue 18
Transcriptomics-based strain optimization tool for designing secondary metabolite overproducing strains of Streptomyces coelicolor: Transcriptomics-based Strain Optimization Tool
journal, September 2015
- Kim, Minsuk; Yi, Jeong Sang; Lakshmanan, Meiyappan
- Biotechnology and Bioengineering, Vol. 113, Issue 3
Computing the functional proteome: recent progress and future prospects for genome-scale models
journal, August 2015
- O’Brien, Edward J.; Palsson, Bernhard O.
- Current Opinion in Biotechnology, Vol. 34
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
A Comparison of the Costs and Benefits of Bacterial Gene Expression
journal, July 2016
- Price, Morgan N.; Wetmore, Kelly M.; Deutschbauer, Adam M.
- PLOS ONE
Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression
journal, January 2017
- Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.
- Scientific Reports, Vol. 7, Issue 1
Current knowledge of the Escherichia coli phosphoenolpyruvate–carbohydrate phosphotransferase system: peculiarities of regulation and impact on growth and product formation
journal, May 2012
- Escalante, Adelfo; Salinas Cervantes, Ania; Gosset, Guillermo
- Applied Microbiology and Biotechnology, Vol. 94, Issue 6
Genome-wide Reconstruction of OxyR and SoxRS Transcriptional Regulatory Networks under Oxidative Stress in Escherichia coli K-12 MG1655
journal, August 2015
- Seo, Sang Woo; Kim, Donghyuk; Szubin, Richard
- Cell Reports, Vol. 12, Issue 8
Global Rebalancing of Cellular Resources by Pleiotropic Point Mutations Illustrates a Multi-scale Mechanism of Adaptive Evolution
journal, April 2016
- Utrilla, Jose; O’Brien, Edward J.; Chen, Ke
- Cell Systems, Vol. 2, Issue 4
Computing the functional proteome: recent progress and future prospects for genome-scale models
journal, August 2015
- O’Brien, Edward J.; Palsson, Bernhard O.
- Current Opinion in Biotechnology, Vol. 34
Methods for integration of transcriptomic data in genome-scale metabolic models
journal, August 2014
- Kim, Min Kyung; Lun, Desmond S.
- Computational and Structural Biotechnology Journal, Vol. 11, Issue 18
Large‐scale 13 C‐flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli
journal, January 2011
- Haverkorn van Rijsewijk, Bart R. B.; Nanchen, Annik; Nallet, Sophie
- Molecular Systems Biology, Vol. 7, Issue 1
Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
journal, November 2002
- Ibarra, Rafael U.; Edwards, Jeremy S.; Palsson, Bernhard O.
- Nature, Vol. 420, Issue 6912
Network-based prediction of human tissue-specific metabolism
journal, August 2008
- Shlomi, Tomer; Cabili, Moran N.; Herrgård, Markus J.
- Nature Biotechnology, Vol. 26, Issue 9
Expanded microbial genome coverage and improved protein family annotation in the COG database
journal, November 2014
- Galperin, Michael Y.; Makarova, Kira S.; Wolf, Yuri I.
- Nucleic Acids Research, Vol. 43, Issue D1
A Comparison of the Costs and Benefits of Bacterial Gene Expression
journal, July 2016
- Price, Morgan N.; Wetmore, Kelly M.; Deutschbauer, Adam M.
- PLOS ONE
Robust flux balance analysis of multiscale biochemical reaction networks
journal, July 2013
- Sun, Yuekai; Fleming, Ronan MT; Thiele, Ines
- BMC Bioinformatics, Vol. 14, Issue 1
Hierarchy of non-glucose sugars in Escherichia coli
journal, December 2014
- Aidelberg, Guy; Towbin, Benjamin D.; Rothschild, Daphna
- BMC Systems Biology, Vol. 8, Issue 1
Shrinking the Metabolic Solution Space Using Experimental Datasets
journal, August 2012
- Reed, Jennifer L.
- PLoS Computational Biology, Vol. 8, Issue 8
Quantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments
journal, June 2016
- O’Brien, Edward J.; Utrilla, Jose; Palsson, Bernhard O.
- PLOS Computational Biology, Vol. 12, Issue 6
Multiscale Modeling of Metabolism and Macromolecular Synthesis in E. coli and Its Application to the Evolution of Codon Usage
journal, September 2012
- Thiele, Ines; Fleming, Ronan M. T.; Que, Richard
- PLoS ONE, Vol. 7, Issue 9
Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
journal, February 2015
- Hui, Sheng; Silverman, Josh M.; Chen, Stephen S.
- Molecular Systems Biology, Vol. 11, Issue 2
Works referencing / citing this record:
Genome-scale metabolic models applied to human health and disease: Genome-scale metabolic models
journal, June 2017
- Cook, Daniel J.; Nielsen, Jens
- Wiley Interdisciplinary Reviews: Systems Biology and Medicine, Vol. 9, Issue 6
Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth
journal, July 2017
- Reimers, Alexandra-M.; Knoop, Henning; Bockmayr, Alexander
- Proceedings of the National Academy of Sciences, Vol. 114, Issue 31
Formation of dominant mode by evolution in biological systems
journal, April 2018
- Furusawa, Chikara; Kaneko, Kunihiko
- Physical Review E, Vol. 97, Issue 4
Machine and deep learning meet genome-scale metabolic modeling
journal, July 2019
- Zampieri, Guido; Vijayakumar, Supreeta; Yaneske, Elisabeth
- PLOS Computational Biology, Vol. 15, Issue 7
Genome-scale model of metabolism and gene expression provides a multi-scale description of acid stress responses in Escherichia coli
journal, December 2019
- Du, Bin; Yang, Laurence; Lloyd, Colton J.
- PLOS Computational Biology, Vol. 15, Issue 12
A quantitative method for proteome reallocation using minimal regulatory interventions
journal, July 2020
- Lastiri-Pancardo, Gustavo; Mercado-Hernández, Jonathan S.; Kim, Juhyun
- Nature Chemical Biology, Vol. 16, Issue 9
DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression
journal, January 2019
- Yang, Laurence; Ebrahim, Ali; Lloyd, Colton J.
- BMC Systems Biology, Vol. 13, Issue 1
Formation of Dominant Mode by Evolution in Biological Systems
journal, October 2017
- Furusawa, Chikara; kaneko, Kunihiko
- Physical Review E
Machine and deep learning meet genome-scale metabolic modeling
journal, July 2019
- Zampieri, Guido; Vijayakumar, Supreeta; Yaneske, Elisabeth
- PLOS Computational Biology, Vol. 15, Issue 7
Genome-scale model of metabolism and gene expression provides a multi-scale description of acid stress responses in Escherichia coli
journal, December 2019
- Du, Bin; Yang, Laurence; Lloyd, Colton J.
- PLOS Computational Biology, Vol. 15, Issue 12