Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation
Year: 2020
Type: article
Abstract: enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle-and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.
Source: Science
Authors: Derek N. Macklin, Travis A. Ahn-Horst, Heejo Choi, Nicholas A. Ruggero, Javier Carrera, John C. Mason, Gwanggyu Sun, Eran Agmon, Mialy M. DeFelice, Inbal Maayan, Keara Lane, Ryan K. Spangler, Taryn E. Gillies, Morgan L. Paull, Sajia Akhter, Samuel R. Bray, Daniel S. Weaver, Ingrid M. Keseler, Peter D. Karp, Jerry H. Morrison, Markus W. Covert
Institutions: Stanford University, SRI International
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, U.S. Department of Energy, Agilent Foundation, Paul G. Allen Family Foundation, Stanford University, Thomas and Stacey Siebel Foundation, National Institutes of Health, National Institute of Standards and Technology, National Institute of General Medical Sciences, U.S. National Library of Medicine
Awards: MARC PREDOCTORAL FELLOWSHIP, COMPUTATIONAL SCIENCE GRADUATE FELLOWSHIP PROGRAM, Deep Curation via an Integrated Whole-Cell Computational Model, G4580178314, A Gene-Complete Computational Model of Yeast, The EcoCyc Model Organism Database for Escherichia coli, Systems Biology of Collective Cell Decisions, The EcoCyc Model Organism Database for Escherichia coli [SRI Proposal ECU 14-631], G6942868959, STANFORD NIST JIMB TRAINING GRANT, A Gene-Complete Computational Model of Yeast, G9000017368
OpenAlex ID: W3044339796