Distributed classifier based on genetically engineered bacterial cell cultures

We describe a conceptual design of a distributed classifier formed by a population of genetically engineered microbial cells. The central idea is to create a complex classifier from a population of weak or simple classifiers. We create a master population of cells with randomized synthetic biosensor circuits that have a broad range of sensitivities towards chemical signals of interest that form the input vectors subject to classification. The randomized sensitivities are achieved by constructing a library of synthetic gene circuits with randomized control sequences (e.g. ribosome-binding sites) in the front element. The training procedure consists in re-shaping of the master population in such a way that it collectively responds to the "positive" patterns of input signals by producing above-threshold output (e.g. fluorescent signal), and below-threshold output in case of the "negative" patterns. The population re-shaping is achieved by presenting sequential examples and pruning the population using either graded selection/counterselection or by fluorescence-activated cell sorting (FACS). We demonstrate the feasibility of experimental implementation of such system computationally using a realistic model of the synthetic sensing gene circuits.Comment: 31 pages, 9 figure

Orthogonal Modular Gene Repression in Escherichia coli Using Engineered CRISPR/Cas9

The progress in development of synthetic gene circuits has been hindered by the limited repertoire of available transcription factors. Recently, it has been greatly expanded using the CRISPR/Cas9 system. However, this system is limited by its imperfect DNA sequence specificity, leading to potential crosstalk with host genome or circuit components. Furthermore, CRISPR/Cas9-mediated gene regulation is context dependent, affecting the modularity of Cas9-based transcription factors. In this paper we address the problems of specificity and modularity by developing a computational approach for selecting Cas9/gRNA transcription factor/promoter pairs that are maximally orthogonal to each other as well as to the host genome and synthetic circuit components. We validate the method by designing and experimentally testing four orthogonal promoter/repressor pairs in the context of a strong promoter P_L from phage lambda. We demonstrate that these promoters can be interfaced by constructing double and triple inverter circuits. To address the problem of modularity we propose and experimentally validate a scheme to predictably incorporate orthogonal CRISPR/Cas9 regulation into a large class of natural promoters

Rapid and Scalable Preparation of Bacterial Lysates for Cell-Free Gene Expression

Cell-free gene expression systems are emerging as an important platform for a diverse range of synthetic biology and biotechnology applications, including production of robust field-ready biosensors. Here, we combine programmed cellular autolysis with a freeze–thaw or freeze-dry cycle to create a practical, reproducible, and a labor- and cost-effective approach for rapid production of bacterial lysates for cell-free gene expression. Using this method, robust and highly active bacterial cell lysates can be produced without specialized equipment at a wide range of scales, making cell-free gene expression easily and broadly accessible. Moreover, live autolysis strain can be freeze-dried directly and subsequently lysed upon rehydration to produce active lysate. We demonstrate the utility of autolysates for synthetic biology by regulating protein production and degradation, implementing quorum sensing, and showing quantitative protection of linear DNA templates by GamS protein. To allow versatile and sensitive β-galactosidase (LacZ) based readout we produce autolysates with no detectable background LacZ activity and use them to produce sensitive mercury­(II) biosensors with LacZ-mediated colorimetric and fluorescent outputs. The autolysis approach can facilitate wider adoption of cell-free technology for cell-free gene expression as well as other synthetic biology and biotechnology applications, such as metabolic engineering, natural product biosynthesis, or proteomics