A sensing array of radically coupled genetic ‘biopixels’

Abstract

While there has been significant progress in the development of engineering principles for synthetic biology, a substantial challenge is the construction of robust circuits in a noisy cellular environment. Such an environment leads to considerable intercellular variability in circuit behavior, which can hinder functionality at the colony level. Here, we engineer the synchronization of thousands of oscillating colony “biopixels” over centimetre length scales through the use of synergistic intercellular coupling involving quorum sensing within a colony and gas-phase redox signaling between colonies. We use this platform to construct an LCD-like macroscopic clock that can be used to sense arsenic via modulation of the oscillatory period. Given the repertoire of sensing capabilities of bacteria such as E. coli, the ability to coordinate their behavior over large length scales sets the stage for the construction of low cost genetic biosensors that are capable of detecting heavy metals and pathogens in the field.

Engineering of regulated stochastic cell fate determination

“…Much effort in synthetic biology has been focused on using synthetic GRNs to drive natural GRNs toward desired responses (27,44). Here, by linking outputs of natural metabolism regulations to synthetic GRNs, we were able to realize an initial condition that is difficult to achieve through engineering alone.…”

Disorder induces explosive synchronization

“…While these transitions were eventually proven to be continuous, and thus not explosive [3,4], interest in abrupt phase transitions was reignited in the context of synchronization [5]. Synchronization has long served as a major tool in studying emergent collective behavior in ensembles of coupled dynamical agents [6,7], with examples found in nature, e.g., rhythmic flashing of fireflies [8] and mammalian circadian rhythms [9], in engineering, e.g., power grids [10] and oscillations of pedestrian bridges [11], and at their intersection, e.g., synthetic cell engineering [12]. In particular, the Kuramoto model has served as a paradigm for both modeling and understanding synchronization [13].…”

Optimal Synchronization of Complex Networks

“…PACS numbers: 05.45.Xt, 89.75.Hc A central goal of complexity theory is to understand the emergence of collective behavior in large ensembles of interacting dynamical systems. Synchronization of networkcoupled oscillators has served as a paradigm for understanding emergence [1][2][3][4], where examples arise in nature (e.g., flashing of fireflies [5] and cardiac pacemaker cells [6]), engineering (e.g., power grid [7] and bridge oscillations [8]), and at their intersection (e.g., synthetic cell engineering [9]). We consider the dynamics of N network-coupled phase oscillators θ i for i = 1, .…”