TY - JOUR
T1 - Bacterial social interactions drive the emergence of differential spatial colony structures
AU - Blanchard, Andrew E.
AU - Lu, Ting
N1 - Funding Information:
This work was supported in part by American Heart Association (Grant No. 12SDG12090025), Brain & Behavior Research Foundation, National Science Foundation (No. 1227034), and T.L.’s startup fund from the University of Illinois at Urbana-Champaign. We are very grateful for tremendous help from Dr. Dmitri Volfson, Dr. Will Mather, Dr. Lev Tsimring, Dr. P. J. Steiner and Dr. Jeff Hasty.
Publisher Copyright:
© 2015 Blanchard and Lu.
PY - 2015/9/16
Y1 - 2015/9/16
N2 - Background: Social interactions have been increasingly recognized as one of the major factors that contribute to the dynamics and function of bacterial communities. To understand their functional roles and enable the design of robust synthetic consortia, one fundamental step is to determine the relationship between the social interactions of individuals and the spatiotemporal structures of communities. Results: We present a systematic computational survey on this relationship for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. We found that deleterious interactions cause an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a smooth expanding front. We also found that mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. In addition, a simplified mathematical model was developed to provide an analytical interpretation of the findings. Conclusions: This work advances our fundamental understanding of bacterial social interactions and population structures and, simultaneously, benefits synthetic biology for facilitated engineering of artificial microbial consortia.
AB - Background: Social interactions have been increasingly recognized as one of the major factors that contribute to the dynamics and function of bacterial communities. To understand their functional roles and enable the design of robust synthetic consortia, one fundamental step is to determine the relationship between the social interactions of individuals and the spatiotemporal structures of communities. Results: We present a systematic computational survey on this relationship for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. We found that deleterious interactions cause an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a smooth expanding front. We also found that mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. In addition, a simplified mathematical model was developed to provide an analytical interpretation of the findings. Conclusions: This work advances our fundamental understanding of bacterial social interactions and population structures and, simultaneously, benefits synthetic biology for facilitated engineering of artificial microbial consortia.
KW - Bacterial colonies
KW - Community structures
KW - Social interactions
KW - Spatiotemporal patterns
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U2 - 10.1186/s12918-015-0188-5
DO - 10.1186/s12918-015-0188-5
M3 - Article
C2 - 26377684
AN - SCOPUS:84941626864
SN - 1752-0509
VL - 9
JO - BMC Systems Biology
JF - BMC Systems Biology
IS - 1
M1 - 59
ER -