Additional file 1 of Bacterial social interactions drive the emergence of differential spatial colony structures

Supporting Information. The file contains two text sections detailing the equations and parameters used for simulations and ODE analysis. Figures S1–S24 and Tables S1–S9 are included with further simulation data

Cloning and Optimization of a Nisin Biosynthesis Pathway for Bacteriocin Harvest

Nisin is an important antimicrobial peptide that has enormous applications in biotechnology. Despite many encouraging efforts, its overproduction has been a long-standing challenge due to the complexity of the underlying pathway and the difficulty in genetic modification of lactic acid bacteria. Here, we cloned an entire nisin biosynthesis pathway from a nisin-producing strain (<i>Lactococcus lactis</i> K29) into a plasmid and transplanted the plasmid into a nisin deficient strain <i>Lactococcus lactis</i> MG1363, resulting in successful heterologous expression of bioactive recombinant nisin. To increase nisin harvest, we also overexpressed nisA, a gene responsible for nisin precursor production, with a set of constitutive promoters. To further optimize nisin yield, we minimized the metabolic cost of the engineered strains by integrating nisA overexpression cassettes and the recombinant pathway into a single circuit. With our rational construction and optimization, our engineered optimized strain is able to produce bioactive nisin with a yield of 1098 IU/mL, which is more than six times higher than that of the original strain

Individual-Based Modeling of Spatial Dynamics of Chemotactic Microbial Populations

One important direction of synthetic biology is to establish desired spatial structures from microbial populations. Underlying this structural development process are different driving factors, among which bacterial motility and chemotaxis serve as a major force. Here, we present an individual-based, biophysical computational framework for mechanistic and multiscale simulation of the spatiotemporal dynamics of motile and chemotactic microbial populations. The framework integrates cellular movement with spatial population growth, mechanical and chemical cellular interactions, and intracellular molecular kinetics. It is validated by a statistical comparison of single-cell chemotaxis simulations with reported experiments. The framework successfully captures colony range expansion of growing isogenic populations and also reveals chemotaxis-modulated, spatial patterns of a two-species amensal community. Partial differential equation-based models subsequently validate these simulation findings. This study provides a versatile computational tool to uncover the fundamentals of microbial spatial ecology as well as to facilitate the design of synthetic consortia for desired spatial patterns

Optimization results for the four test systems.

<p>Optimization results for the four test systems.</p

Input/output logic table for quad-not system.

<p>Input/output logic table for quad-not system.</p

A Proto dataflow computation is compiled to an abstract genetic regulatory network in two stages.

<p>First, each operator is mapped to a motif and each dataflow edge is mapped to a regulatory protein (blue dotted lines). These elements are then linked together using the structure of the dataflow graph to form an abstract genetic regulatory network (red dotted lines).</p

Proto code for a two-bit adder, showing operators in color.

<p>Inputs are purple, logic operators are red, functions are blue-green, and outputs are in their corresponding color.</p

Simulation of automatically generated genetic regulatory networks for the two-bit adder.

<p>The upper graphs show small-molecule input concentrations and the lower three graphs show output CFP, RFP, and GFP concentrations for the optimized (solid blue) and unoptimized (dashed black) networks.</p

Input/output logic table for 2-bit adder system.

<p>Italics show the role of each molecule, per <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022490#pone-0022490-g010" target="_blank">Figure 10</a>.</p

Proto biocompiler architecture and example.

<p>(a) This paper extends the Proto spatial computing language with mechanisms for genetic regulatory network design (pink). (b) An example showing how a simple high level behavioral specification is converted first into a dataflow network, then into a genetic regulatory network, and finally optimized. In this example, green fluorescence is turned ON only when both small molecule inputs aTc and IPTG are not present (aTc, anhydrotetracycline. IPTG, Isopropyl -D-1-thiogalactopyranoside). A–F represent transcriptional repressors to be chosen later from a parts library.</p