Emergence of microbial networks as response to hostile environments

被引:10
作者
Madeo, Dario [1 ]
Comolli, Luis R. [2 ]
Mocenni, Chiara [1 ]
机构
[1] Univ Siena, Dept Informat Engn & Math, I-53100 Siena, Italy
[2] Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Biol Struct & Imaging Dept, Div Life Sci, Berkeley, CA 94720 USA
关键词
microbial communities; bacterial social networks; evolutionary games; graph theory; evolutive decisions; hostile environmental conditions; BACTERIAL; EVOLUTION;
D O I
10.3389/fmicb.2014.00407
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
The majority of microorganisms live in complex communities under varying conditions. One pivotal question in evolutionary biology is the emergence of cooperative traits and their sustainment in altered environments or in the presence of free-riders. Co-occurrence patterns in the spatial distribution of biofilms can help define species' identities, and systems biology tools are revealing networks of interacting microorganisms. However, networks of inter-dependencies involving micro-organisms in the planktonic phase may be just as important, with the added complexity that they are not bounded in space. An integrated approach linking imaging, "Omics" and modeling has the potential to enable new hypothesis and working models. In order to understand how cooperation can emerge and be maintained without abilities like memory or recognition we use evolutionary game theory as the natural framework to model cell-cell interactions arising from evolutive decisions. We consider a finite population distributed in a spatial domain (biofilm), and divided into two interacting classes with different traits. This interaction can be weighted by distance, and produces physical connections between two elements allowing them to exchange finite amounts of energy and matter. Available strategies to each individual of one class in the population are the propensities or "willingness" to connect any individual of the other class. Following evolutionary game theory, we propose a mathematical model which explains the patterns of connections which emerge when individuals are able to find connection strategies that asymptotically optimize their fitness. The process explains the formation of a network for efficiently exchanging energy and matter among individuals and thus ensuring their survival in hostile environments.
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页数:13
相关论文
共 20 条
[1]   Enigmatic, ultrasmall, uncultivated Archaea [J].
Baker, Brett J. ;
Comolli, Luis R. ;
Dick, Gregory J. ;
Hauser, Loren J. ;
Hyatt, Doug ;
Dill, Brian D. ;
Land, Miriam L. ;
VerBerkmoes, Nathan C. ;
Hettich, Robert L. ;
Banfield, Jillian F. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2010, 107 (19) :8806-8811
[2]   Bacterial cooperative organization under antibiotic stress [J].
Ben-Jacob, E ;
Cohen, I ;
Golding, I ;
Gutnick, DL ;
Tcherpakov, M ;
Helbing, D ;
Ron, IG .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2000, 282 (1-2) :247-282
[3]  
Ben-Jacob E., 1997, BACTERIA MULTICELLUL, P394
[4]   Inter-species interconnections in acid mine drainage microbial communities [J].
Comolli, Luis R. ;
Banfield, Jill F. .
FRONTIERS IN MICROBIOLOGY, 2014, 5
[5]   Intercellular Nanotubes Mediate Bacterial Communication [J].
Dubey, Gyanendra P. ;
Ben-Yehuda, Sigal .
CELL, 2011, 144 (04) :590-600
[6]   Networking Opportunities for Bacteria [J].
Dwyer, Daniel J. ;
Kohanski, Michael A. ;
Collins, James J. .
CELL, 2008, 135 (07) :1153-1156
[7]   Crawling into a new era -: the Dictyostelium genome project [J].
Eichinger, L ;
Noegel, AA .
EMBO JOURNAL, 2003, 22 (09) :1941-1946
[8]   Evolutionary game theory: Theoretical concepts and applications to microbial communities [J].
Frey, Erwin .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2010, 389 (20) :4265-4298
[9]   Microbial community structure and its functional implications [J].
Fuhrman, Jed A. .
NATURE, 2009, 459 (7244) :193-199
[10]   Driving Biofuels from Field to Fuel Tank [J].
Gura, Trisha .
CELL, 2009, 138 (01) :9-12