TY - JOUR
T1 - Queuing Models for Abstracting Interactions in Bacterial Communities
AU - Michelusi, Nicolo
AU - Boedicker, James
AU - El-Naggar, Mohamed Y.
AU - Mitra, Urbashi
N1 - Funding Information:
The work of N. Michelusi and U. Mitra was supported by one or all of these grants: ONR N00014-09-1-0700, CCF-0917343, CCF-1117896, CNS-1213128, AFOSR FA9550-12-1-0215, and DOT CA-26-7084-00. The work of J. Boedicker was supported by the ONR award N00014-15-1-2573. The work of M. Y. El-Naggar was supported by the NASA Cooperative Agreement NNA13AA92A and PECASE award FA955014-1-0294 from the Air Force Office of Scientific Research.
Publisher Copyright:
© 1983-2012 IEEE.
PY - 2016/3
Y1 - 2016/3
N2 - Microbial communities play a significant role in bioremediation, plant growth, human and animal digestion, global elemental cycles including the carbon-cycle, and water treatment. They are also posed to be the engines of renewable energy via microbial fuel cells, which can reverse the process of electrosynthesis. Microbial communication regulates many virulence mechanisms used by bacteria. Thus, it is of fundamental importance to understand interactions in microbial communities and to develop predictive tools that help control them, in order to aid the design of systems exploiting bacterial capabilities. This position paper explores how abstractions from communications, networking and information theory can play a role in understanding and modeling bacterial interactions. In particular, two forms of interactions in bacterial systems will be examined: electron transfer and quorum sensing. While the diffusion of chemical signals has been heavily studied, electron transfer occurring in living cells and its role in cell-cell interaction is less understood. Recent experimental observations open up new frontiers in the design of microbial systems based on electron transfer, which may coexist with the more well-known interaction strategies based on molecular diffusion. In quorum sensing, the concentration of certain signature chemical compounds emitted by the bacteria is used to estimate the bacterial population size, so as to activate collective behaviors. In this position paper, queuing models for electron transfer are summarized and adapted to provide new models for quorum sensing. These models are stochastic, and thus capture the inherent randomness exhibited by cell colonies in nature. It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment, thus enabling the construction of an information theoretic framework, while being amenable to complexity reduction using methods based on statistical physics and wireless network design.
AB - Microbial communities play a significant role in bioremediation, plant growth, human and animal digestion, global elemental cycles including the carbon-cycle, and water treatment. They are also posed to be the engines of renewable energy via microbial fuel cells, which can reverse the process of electrosynthesis. Microbial communication regulates many virulence mechanisms used by bacteria. Thus, it is of fundamental importance to understand interactions in microbial communities and to develop predictive tools that help control them, in order to aid the design of systems exploiting bacterial capabilities. This position paper explores how abstractions from communications, networking and information theory can play a role in understanding and modeling bacterial interactions. In particular, two forms of interactions in bacterial systems will be examined: electron transfer and quorum sensing. While the diffusion of chemical signals has been heavily studied, electron transfer occurring in living cells and its role in cell-cell interaction is less understood. Recent experimental observations open up new frontiers in the design of microbial systems based on electron transfer, which may coexist with the more well-known interaction strategies based on molecular diffusion. In quorum sensing, the concentration of certain signature chemical compounds emitted by the bacteria is used to estimate the bacterial population size, so as to activate collective behaviors. In this position paper, queuing models for electron transfer are summarized and adapted to provide new models for quorum sensing. These models are stochastic, and thus capture the inherent randomness exhibited by cell colonies in nature. It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment, thus enabling the construction of an information theoretic framework, while being amenable to complexity reduction using methods based on statistical physics and wireless network design.
KW - Quorum sensing
KW - bacterial interactions
KW - electron transfer
KW - queuing models
KW - stochastic modeling
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U2 - 10.1109/JSAC.2016.2525558
DO - 10.1109/JSAC.2016.2525558
M3 - Article
AN - SCOPUS:84963773718
VL - 34
SP - 584
EP - 599
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
SN - 0733-8716
IS - 3
M1 - 7397847
ER -