DocumentCode
3124805
Title
Collective sensing-capacity of bacteria populations
Author
Einolghozati, Arash ; Sardari, Mohsen ; Fekri, Faramarz
Author_Institution
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear
2012
fDate
1-6 July 2012
Firstpage
2959
Lastpage
2963
Abstract
The design of biological networks using bacteria as the basic elements of the network is initially motivated by a phenomenon called quorum sensing. Through quorum sensing, each bacterium performs sensing the medium and communicating it to others via molecular communication. As a result, bacteria can orchestrate and act collectively and perform tasks impossible otherwise. In this paper, we consider a population of bacteria as a single node in a network. In our version of biological communication networks, such a node would communicate with one another via molecular signals. As a first step toward such networks, this paper focuses on the study of the transfer of information to the population (i.e., the node) by stimulating it with a concentration of special type of a molecules signal. These molecules trigger a chain of processes inside each bacteria that results in a final output in the form of light or fluorescence. Each stage in the process adds noise to the signal carried to the next stage. Our objective is to measure (compute) the maximum amount of information that we can transfer to the node. This can be viewed as the collective sensing capacity of the node. The molecular concentration, which carries the information, is the input to the node, which should be estimated by observing the produced light as the output of the node (i.e., the entire population of bacteria forming the node. The molecules are trapped in the bacteria receptors forming complexes inside the bacteria which affect the genes responsible for producing the light. We focus on the noise caused by the random process of trapping molecules at the receptors as well as the variation of outputs of different bacteria in the node. The optimal input distribution to maximize the mutual information between the output of the node, e.g., light, and the applied molecule concentration is derived. Further, the capacity variation with the number of bacteria in the node and the number of receptors per bacteria is o- tained. Finally, we investigated the collective sensing capability of the node when a specific form of molecular signaling concentration (which resembles M-ary modulation) is used. The achievable sensing capacity and the corresponding error probabilities were obtained for such practical signaling techniques.
Keywords
bio-optics; biosensors; fluorescence; genetics; microorganisms; molecular biophysics; probability; random noise; M-ary modulation; bacteria populations; biological communication networks; collective sensing-capacity; error probabilities; fluorescence; genes; light; molecular communication; molecular concentration; molecular signaling concentration; optimal input distribution; practical signaling techniques; quorum sensing; random noise; Microorganisms; Modulation; Molecular communication; Noise; Sensors; Sociology; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
Conference_Location
Cambridge, MA
ISSN
2157-8095
Print_ISBN
978-1-4673-2580-6
Electronic_ISBN
2157-8095
Type
conf
DOI
10.1109/ISIT.2012.6284080
Filename
6284080
Link To Document