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פותח על ידי קלירמאש פתרונות בע"מ -
Metabolic-network-driven analysis of bacterial ecological strategies
Year:
2009
Source of publication :
Genome Biology
Authors :
פרייליך, שירי
;
.
Volume :
10
Co-Authors:
Freilich, S., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel, School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Kreimer, A., School of Mathematical Science, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Borenstein, E., Department of Biological Sciences, Stanford University, Stanford, CA 94305-5020, United States, Santa Fe Institute, Santa Fe, NM 87501, United States
Yosef, N., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Sharan, R., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Gophna, U., Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Ruppin, E., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel, School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Facilitators :
From page:
To page:
(
Total pages:
1
)
Abstract:
Background: The growth-rate of an organism is an important phenotypic trait, directly affecting its ability to survive in a given environment. Here we present the first large scale computational study of the association between ecological strategies and growth rate across 113 bacterial species, occupying a variety of metabolic habitats. Genomic data are used to reconstruct the species' metabolic networks and habitable metabolic environments. These reconstructions are then used to investigate the typical ecological strategies taken by organisms in terms of two basic species-specific measures: metabolic variability - the ability of a species to survive in a variety of different environments; and co-habitation score vector - the distribution of other species that co-inhabit each environment. Results: We find that growth rate is significantly correlated with metabolic variability and the level of co-habitation (that is, competition) encountered by an organism. Most bacterial organisms adopt one of two main ecological strategies: a specialized niche with little co-habitation, associated with a typically slow rate of growth; or ecological diversity with intense co-habitation, associated with a typically fast rate of growth. Conclusions: The pattern observed suggests a universal principle where metabolic flexibility is associated with a need to grow fast, possibly in the face of competition. This new ability to produce a quantitative description of the growth rate-metabolism-community relationship lays a computational foundation for the study of a variety of aspects of the communal metabolic life. © 2009 Freilich et al.; licensee BioMed Central Ltd.
Note:
Related Files :
bacteria
Genetics
Growth, Development and Aging
metabolism
Models, Biological
species distribution
עוד תגיות
תוכן קשור
More details
DOI :
10.1186/gb-2009-10-6-r61
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
32202
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 01:08
Scientific Publication
Metabolic-network-driven analysis of bacterial ecological strategies
10
Freilich, S., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel, School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Kreimer, A., School of Mathematical Science, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Borenstein, E., Department of Biological Sciences, Stanford University, Stanford, CA 94305-5020, United States, Santa Fe Institute, Santa Fe, NM 87501, United States
Yosef, N., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Sharan, R., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Gophna, U., Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Ruppin, E., The Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel, School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel
Metabolic-network-driven analysis of bacterial ecological strategies
Background: The growth-rate of an organism is an important phenotypic trait, directly affecting its ability to survive in a given environment. Here we present the first large scale computational study of the association between ecological strategies and growth rate across 113 bacterial species, occupying a variety of metabolic habitats. Genomic data are used to reconstruct the species' metabolic networks and habitable metabolic environments. These reconstructions are then used to investigate the typical ecological strategies taken by organisms in terms of two basic species-specific measures: metabolic variability - the ability of a species to survive in a variety of different environments; and co-habitation score vector - the distribution of other species that co-inhabit each environment. Results: We find that growth rate is significantly correlated with metabolic variability and the level of co-habitation (that is, competition) encountered by an organism. Most bacterial organisms adopt one of two main ecological strategies: a specialized niche with little co-habitation, associated with a typically slow rate of growth; or ecological diversity with intense co-habitation, associated with a typically fast rate of growth. Conclusions: The pattern observed suggests a universal principle where metabolic flexibility is associated with a need to grow fast, possibly in the face of competition. This new ability to produce a quantitative description of the growth rate-metabolism-community relationship lays a computational foundation for the study of a variety of aspects of the communal metabolic life. © 2009 Freilich et al.; licensee BioMed Central Ltd.
Scientific Publication
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