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Wen, K. Y.

Publications and source records attributed to Wen, K. Y..

2 recordsLinked to original sources

Emergent digital bio-computation through spatial diffusion and engineered bacteria

Building computationally capable biological systems has long been an aim of synthetic biology. The potential utility of biocomputing devices ranges from biosafety and environmental applications to diagnosis and personalised medicine. Here we present work for the design of bacterial computers which use spatial patterning to process information. Our computers are composed of bacterial colonies which, inspired by patterning in embryo development, receive information in the form of diffusible morphogen-like signals. A computation is encoded by the physical locations of the input sources of morphogen and the output receiver colonies. We demonstrate, mathematically and with engineered Escherichia coli, the simple digital logic capability of single bacterial colonies and show how additional colonies are required to build complex functions. Inspired by electronic design automation, an algorithm for designing optimal spatial circuits computing two-level digital functions is presented. This enhances the capability of our system to complex digital functions without increasing the biological complexity. We extend our experimental system to incorporate biosensing colonies as morphogen sources, demonstrating how a diagnostic device might be constructed. Our approach will open up new ways to perform biological computation, with applications in bioengineering, biomaterials and biosensing. Ultimately, these computational bacterial communities will help us explore information processing in natural biological systems.

synthetic biology↗

FlopR: An open source software package for calibration and normalization of plate reader and flow cytometry data

The measurement of gene expression using fluorescence markers has been a cornerstone of synthetic biology for the last two decades. However, the use of arbitrary units has limited the usefulness of this data for many quantitative purposes. Calibration of fluorescence measurements from flow cytometry and plate reader spectrophotometry has been implemented previously but the tools are disjointed. Here we pull together, and in some cases improve, extant methods into a single software tool, written as a package in the R statistical framework. The workflow is validated using Escherichia coli engineered to express GFP from a set of commonly used constitutive promoters. We then demonstrate its power by identifying the time evolution of distinct subpopulations of bacteria from bulk plate reader data, a task previously reliant on laborious flow cytometry experiments. Along with standardized parts and experimental methods, the development and dissemination of usable tools for quantitative measurement and data analysis will benefit the synthetic biology community by improving interoperability.Competing Interest StatementThe authors have declared no competing interest.View Full Text

synthetic biology↗