Cargando…

Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms

Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is...

Descripción completa

Detalles Bibliográficos
Autores principales: Zarecki, Raphy, Oberhardt, Matthew A., Yizhak, Keren, Wagner, Allon, Shtifman Segal, Ella, Freilich, Shiri, Henry, Christopher S., Gophna, Uri, Ruppin, Eytan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035307/
https://www.ncbi.nlm.nih.gov/pubmed/24866123
http://dx.doi.org/10.1371/journal.pone.0098372
_version_ 1782318042637664256
author Zarecki, Raphy
Oberhardt, Matthew A.
Yizhak, Keren
Wagner, Allon
Shtifman Segal, Ella
Freilich, Shiri
Henry, Christopher S.
Gophna, Uri
Ruppin, Eytan
author_facet Zarecki, Raphy
Oberhardt, Matthew A.
Yizhak, Keren
Wagner, Allon
Shtifman Segal, Ella
Freilich, Shiri
Henry, Christopher S.
Gophna, Uri
Ruppin, Eytan
author_sort Zarecki, Raphy
collection PubMed
description Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is key to both understanding and manipulating life. Despite this, current methods for predicting microbial fitness typically focus on yields [e.g., predictions of biomass yield using GEnome-scale metabolic Models (GEMs)] or notably require many empirical kinetic constants or substrate uptake rates, which render these methods ineffective in cases where fitness derives most directly from growth rate. Here we present a new method for predicting cellular growth rate, termed SUMEX, which does not require any empirical variables apart from a metabolic network (i.e., a GEM) and the growth medium. SUMEX is calculated by maximizing the SUM of molar EXchange fluxes (hence SUMEX) in a genome-scale metabolic model. SUMEX successfully predicts relative microbial growth rates across species, environments, and genetic conditions, outperforming traditional cellular objectives (most notably, the convention assuming biomass maximization). The success of SUMEX suggests that the ability of a cell to catabolize substrates and produce a strong proton gradient enables fast cell growth. Easily applicable heuristics for predicting growth rate, such as what we demonstrate with SUMEX, may contribute to numerous medical and biotechnological goals, ranging from the engineering of faster-growing industrial strains, modeling of mixed ecological communities, and the inhibition of cancer growth.
format Online
Article
Text
id pubmed-4035307
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-40353072014-06-02 Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms Zarecki, Raphy Oberhardt, Matthew A. Yizhak, Keren Wagner, Allon Shtifman Segal, Ella Freilich, Shiri Henry, Christopher S. Gophna, Uri Ruppin, Eytan PLoS One Research Article Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is key to both understanding and manipulating life. Despite this, current methods for predicting microbial fitness typically focus on yields [e.g., predictions of biomass yield using GEnome-scale metabolic Models (GEMs)] or notably require many empirical kinetic constants or substrate uptake rates, which render these methods ineffective in cases where fitness derives most directly from growth rate. Here we present a new method for predicting cellular growth rate, termed SUMEX, which does not require any empirical variables apart from a metabolic network (i.e., a GEM) and the growth medium. SUMEX is calculated by maximizing the SUM of molar EXchange fluxes (hence SUMEX) in a genome-scale metabolic model. SUMEX successfully predicts relative microbial growth rates across species, environments, and genetic conditions, outperforming traditional cellular objectives (most notably, the convention assuming biomass maximization). The success of SUMEX suggests that the ability of a cell to catabolize substrates and produce a strong proton gradient enables fast cell growth. Easily applicable heuristics for predicting growth rate, such as what we demonstrate with SUMEX, may contribute to numerous medical and biotechnological goals, ranging from the engineering of faster-growing industrial strains, modeling of mixed ecological communities, and the inhibition of cancer growth. Public Library of Science 2014-05-27 /pmc/articles/PMC4035307/ /pubmed/24866123 http://dx.doi.org/10.1371/journal.pone.0098372 Text en © 2014 Zarecki et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zarecki, Raphy
Oberhardt, Matthew A.
Yizhak, Keren
Wagner, Allon
Shtifman Segal, Ella
Freilich, Shiri
Henry, Christopher S.
Gophna, Uri
Ruppin, Eytan
Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms
title Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms
title_full Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms
title_fullStr Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms
title_full_unstemmed Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms
title_short Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms
title_sort maximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035307/
https://www.ncbi.nlm.nih.gov/pubmed/24866123
http://dx.doi.org/10.1371/journal.pone.0098372
work_keys_str_mv AT zareckiraphy maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT oberhardtmatthewa maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT yizhakkeren maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT wagnerallon maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT shtifmansegalella maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT freilichshiri maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT henrychristophers maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT gophnauri maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms
AT ruppineytan maximalsumofmetabolicexchangefluxesoutperformsbiomassyieldasapredictorofgrowthrateofmicroorganisms