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Article

Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics

1
Department of Chemical and Biochemial Engineering, Missouri University of Science and Technology, Rolla, MO 65409, USA
2
Department of Computer Science, Missouri University of Science and Technology, Rolla, MO 65409, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Processes 2018, 6(11), 217; https://doi.org/10.3390/pr6110217
Received: 26 July 2018 / Revised: 29 October 2018 / Accepted: 31 October 2018 / Published: 4 November 2018
(This article belongs to the Special Issue Systems Biomedicine )
Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular functions, such as death, division, or phenotype change. Cell death is implemented by terminating a parallel process, while cell division is carried out by creating a new process (daughter cell) from an existing one (mother cell). We first demonstrate these capabilities by creating two simple example models. In one model, we consider a relatively simple scenario where cells can evolve independently. In the other model, we consider interdependency among the cells, where cellular communication determines their collective behavior and evolution under a temporally evolving growth condition. We then demonstrate the framework’s capability by simulating a full-scale model of bacterial quorum sensing, where the dynamics of a population of bacterial cells is dictated by the intercellular communications in a time-evolving growth environment. View Full-Text
Keywords: multiscale modeling; message passing interface; Gillespie method; cell population dynamics; quorum sensing multiscale modeling; message passing interface; Gillespie method; cell population dynamics; quorum sensing
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MDPI and ACS Style

Islam, M.A.; Roy, S.; Das, S.K.; Barua, D. Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics. Processes 2018, 6, 217. https://doi.org/10.3390/pr6110217

AMA Style

Islam MA, Roy S, Das SK, Barua D. Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics. Processes. 2018; 6(11):217. https://doi.org/10.3390/pr6110217

Chicago/Turabian Style

Islam, Mohammad A., Satyaki Roy, Sajal K. Das, and Dipak Barua. 2018. "Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics" Processes 6, no. 11: 217. https://doi.org/10.3390/pr6110217

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