Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics

• Main Authors: Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua
• Format: Article
• Language: English
• Published: MDPI AG 2018-11-01
• Series: Processes
• Subjects: multiscale modeling; message passing interface; Gillespie method; cell population dynamics; quorum sensing
• Online Access: https://www.mdpi.com/2227-9717/6/11/217

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.