An E. coli display method for characterization of peptide-sensor kinase interactions.

Bacteria use two-component system (TCS) signaling pathways to sense and respond to peptides involved in host defense, quorum sensing and inter-bacterial warfare. However, little is known about the broad peptide-sensing capabilities of TCSs. In this study, we developed an Escherichia coli display method to characterize the effects of human antimicrobial peptides (AMPs) on the pathogenesis-regulating TCS PhoPQ of Salmonella Typhimurium with much higher throughput than previously possible. We found that PhoPQ senses AMPs with diverse sequences, structures and biological functions. We further combined thousands of displayed AMP variants with machine learning to identify peptide sub-domains and biophysical features linked to PhoPQ activation. Most of the newfound AMP activators induce PhoPQ in S. Typhimurium, suggesting possible roles in virulence regulation. Finally, we present evidence that PhoPQ peptide-sensing specificity has evolved across commensal and pathogenic bacteria. Our method enables new insights into the specificities, mechanisms and evolutionary dynamics of TCS-mediated peptide sensing in bacteria.

Real-time detection of response regulator phosphorylation dynamics in live bacteria.

Bacteria utilize two-component system (TCS) signal transduction pathways to sense and adapt to changing environments. In a typical TCS, a stimulus induces a sensor histidine kinase (SHK) to phosphorylate a response regulator (RR), which then dimerizes and activates a transcriptional response. Here, we demonstrate that oligomerization-dependent depolarization of excitation light by fused mNeonGreen fluorescent protein probes enables real-time monitoring of RR dimerization dynamics in live bacteria. Using inducible promoters to independently express SHKs and RRs, we detect RR dimerization within seconds of stimulus addition in several model pathways. We go on to combine experiments with mathematical modeling to reveal that TCS phosphosignaling accelerates with SHK expression but decelerates with RR expression and SHK phosphatase activity. We further observe pulsatile activation of the SHK NarX in response to addition and depletion of the extracellular electron acceptor nitrate when the corresponding TCS is expressed from both inducible systems and the native chromosomal operon. Finally, we combine our method with polarized light microscopy to enable single-cell measurements of RR dimerization under changing stimulus conditions. Direct in vivo characterization of RR oligomerization dynamics should enable insights into the regulation of bacterial physiology.

A synthetic genetic edge detection program.

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

Mucosal acidosis elicits a unique molecular signature in epithelia and intestinal tissue mediated by GPR31-induced CREB phosphorylation.

Metabolic changes associated with tissue inflammation result in significant extracellular acidosis (EA). Within mucosal tissues, intestinal epithelial cells (IEC) have evolved adaptive strategies to cope with EA through the up-regulation of SLC26A3 to promote pH homeostasis. We hypothesized that EA significantly alters IEC gene expression as an adaptive mechanism to counteract inflammation. Using an unbiased RNA sequencing approach, we defined the impact of EA on IEC gene expression to define molecular mechanisms by which IEC respond to EA. This approach identified a unique gene signature enriched in cyclic AMP response element-binding protein (CREB)-regulated gene targets. Utilizing loss- and gain-of-function approaches in cultured epithelia and murine colonoids, we demonstrate that EA elicits prominent CREB phosphorylation through cyclic AMP-independent mechanisms that requires elements of the mitogen-activated protein kinase signaling pathway. Further analysis revealed that EA signals through the G protein-coupled receptor GPR31 to promote induction of FosB, NR4A1, and DUSP1. These studies were extended to an in vivo murine model in conjunction with colonization of a pH reporter Escherichia coli strain that demonstrated significant mucosal acidification in the TNFΔARE model of murine ileitis. Herein, we observed a strong correlation between the expression of acidosis-associated genes with bacterial reporter sfGFP intensity in the distal ileum. Finally, the expression of this unique EA-associated gene signature was increased during active inflammation in patients with Crohn's disease but not in the patient control samples. These findings establish a mechanism for EA-induced signals during inflammation-associated acidosis in both murine and human ileitis.

Multiplexing cell-cell communication.

The engineering of advanced multicellular behaviors, such as the programmed growth of biofilms or tissues, requires cells to communicate multiple aspects of physiological information. Unfortunately, few cell-cell communication systems have been developed for synthetic biology. Here, we engineer a genetically encoded channel selector device that enables a single communication system to transmit two separate intercellular conversations. Our design comprises multiplexer and demultiplexer sub-circuits constructed from a total of 12 CRISPRi-based transcriptional logic gates, an acyl homoserine lactone-based communication module, and three inducible promoters that enable small molecule control over the conversations. Experimentally parameterized mathematical models of the sub-components predict the steady state and dynamical performance of the full system. Multiplexed cell-cell communication has applications in synthetic development, metabolic engineering, and other areas requiring the coordination of multiple pathways among a community of cells.

Rewiring bacterial two-component systems by modular DNA-binding domain swapping.

Two-component systems (TCSs) are the largest family of multi-step signal transduction pathways and valuable sensors for synthetic biology. However, most TCSs remain uncharacterized or difficult to harness for applications. Major challenges are that many TCS output promoters are unknown, subject to cross-regulation, or silent in heterologous hosts. Here, we demonstrate that the two largest families of response regulator DNA-binding domains can be interchanged with remarkable flexibility, enabling the corresponding TCSs to be rewired to synthetic output promoters. We exploit this plasticity to eliminate cross-regulation, un-silence a gram-negative TCS in a gram-positive host, and engineer a system with over 1,300-fold activation. Finally, we apply DNA-binding domain swapping to screen uncharacterized Shewanella oneidensis TCSs in Escherichia coli, leading to the discovery of a previously uncharacterized pH sensor. This work should accelerate fundamental TCS studies and enable the engineering of a large family of genetically encoded sensors with diverse applications.

A Miniaturized Escherichia coli Green Light Sensor with High Dynamic Range.

Genetically engineered photoreceptors enable unrivaled control over gene expression. Previously, we ported the Synechocystis PCC 6803 CcaSR two-component system, which is activated by green light and deactivated by red, into Escherichia coli, resulting in a sensor with a sixfold dynamic range. Later, we optimized pathway protein expression levels and the output promoter sequence to decrease transcriptional leakiness and to increase the dynamic range to approximately 120-fold. These CcaSR v 1.0 and v 2.0 systems have been used for precise quantitative, temporal, and spatial control of gene expression for a variety of applications. Recently, other workers deleted two PAS domains of unknown function from the CcaS sensor histidine kinase in a system similar to CcaSR v 1.0. Here we apply these deletions to CcaSR v 2.0, resulting in a v 3.0 light sensor with an output four times less leaky and a dynamic range of nearly 600-fold. We demonstrate that the PAS domain deletions have no deleterious effect on CcaSR green light sensitivity or response dynamics. CcaSR v 3.0 is the best-performing engineered bacterial green light sensor available, and should have broad applications in fundamental and synthetic biology studies.

A photoconversion model for full spectral programming and multiplexing of optogenetic systems.

Optogenetics combines externally applied light signals and genetically engineered photoreceptors to control cellular processes with unmatched precision. Here, we develop a mathematical model of wavelength- and intensity-dependent photoconversion, signaling, and output gene expression for our two previously engineered light-sensing Escherichia coli two-component systems. To parameterize the model, we develop a simple set of spectral and dynamical calibration experiments using our recent open-source "Light Plate Apparatus" device. In principle, the parameterized model should predict the gene expression response to any time-varying signal from any mixture of light sources with known spectra. We validate this capability experimentally using a suite of challenging light sources and signals very different from those used during the parameterization process. Furthermore, we use the model to compensate for significant spectral cross-reactivity inherent to the two sensors in order to develop a new method for programming two simultaneous and independent gene expression signals within the same cell. Our optogenetic multiplexing method will enable powerful new interrogations of how metabolic, signaling, and decision-making pathways integrate multiple input signals.

Engineering bacterial thiosulfate and tetrathionate sensors for detecting gut inflammation.

There is a groundswell of interest in using genetically engineered sensor bacteria to study gut microbiota pathways, and diagnose or treat associated diseases. Here, we computationally identify the first biological thiosulfate sensor and an improved tetrathionate sensor, both two-component systems from marine Shewanella species, and validate them in laboratory Escherichia coli Then, we port these sensors into a gut-adapted probiotic E. coli strain, and develop a method based upon oral gavage and flow cytometry of colon and fecal samples to demonstrate that colon inflammation (colitis) activates the thiosulfate sensor in mice harboring native gut microbiota. Our thiosulfate sensor may have applications in bacterial diagnostics or therapeutics. Finally, our approach can be replicated for a wide range of bacterial sensors and should thus enable a new class of minimally invasive studies of gut microbiota pathways.

Reverse transduction can improve efficiency of AAV vectors in transduction-resistant cells.

Reverse transduction, also known as substrate-mediated gene delivery, is a strategy in which viral vectors are first coated onto a surface that subsequently comes into contact with mammalian cells. The cells internalize the surface-attached vectors, resulting in transgene expression. We hypothesized that forcing the interaction between cells and adeno-associated virus (AAV) vectors through a reverse transduction format would increase in vitro gene delivery efficiencies of the vectors in transduction-resistant cells. We tested this hypothesis by comparing the gene delivery efficiencies of three AAV serotypes using either standard or reverse transduction approaches. Our study reveals reverse transduction of AAV7 and AAV9 can significantly improve their delivery efficiencies. In contrast, AAV2 does not perform better under the reverse transduction format. Interestingly, increased vector uptake by cells does not provide a complete explanation for the increased transduction efficiency. Our findings offer a simple and practical method for improving transduction outcomes in vitro in cell types less permissive to a particular AAV vector.

Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals.

Gene circuits are dynamical systems that regulate cellular behaviors, often using protein signals as inputs and outputs. Here we have developed an optogenetic 'function generator' method for programming tailor-made gene expression signals in live bacterial cells. We designed precomputed light sequences based on experimentally calibrated mathematical models of light-switchable two-component systems and used them to drive intracellular protein levels to match user-defined reference time courses. We used this approach to generate accelerated and linearized dynamics, sinusoidal oscillations with desired amplitudes and periods, and a complex waveform, all with unprecedented accuracy and precision. We also combined the function generator with a dual fluorescent protein reporter system, analogous to a dual-channel oscilloscope, to reveal that a synthetic repressible promoter linearly transforms repressor signals with an approximate 7-min delay. Our approach will enable a new generation of dynamical analyses of synthetic and natural gene circuits, providing an essential step toward the predictive design and rigorous understanding of biological systems.

Robust multicellular computing using genetically encoded NOR gates and chemical 'wires'.

Computation underlies the organization of cells into higher-order structures, for example during development or the spatial association of bacteria in a biofilm. Each cell performs a simple computational operation, but when combined with cell-cell communication, intricate patterns emerge. Here we study this process by combining a simple genetic circuit with quorum sensing to produce more complex computations in space. We construct a simple NOR logic gate in Escherichia coli by arranging two tandem promoters that function as inputs to drive the transcription of a repressor. The repressor inactivates a promoter that serves as the output. Individual colonies of E. coli carry the same NOR gate, but the inputs and outputs are wired to different orthogonal quorum-sensing 'sender' and 'receiver' devices. The quorum molecules form the wires between gates. By arranging the colonies in different spatial configurations, all possible two-input gates are produced, including the difficult XOR and EQUALS functions. The response is strong and robust, with 5- to >300-fold changes between the 'on' and 'off' states. This work helps elucidate the design rules by which simple logic can be harnessed to produce diverse and complex calculations by rewiring communication between cells.

Optogenetic characterization methods overcome key challenges in synthetic and systems biology.

Systems biologists aim to understand how organism-level processes, such as differentiation and multicellular development, are encoded in DNA. Conversely, synthetic biologists aim to program systems-level biological processes, such as engineered tissue growth, by writing artificial DNA sequences. To achieve their goals, these groups have adapted a hierarchical electrical engineering framework that can be applied in the forward direction to design complex biological systems or in the reverse direction to analyze evolved networks. Despite much progress, this framework has been limited by an inability to directly and dynamically characterize biological components in the varied contexts of living cells. Recently, two optogenetic methods for programming custom gene expression and protein localization signals have been developed and used to reveal fundamentally new information about biological components that respond to those signals. This basic dynamic characterization approach will be a major enabling technology in synthetic and systems biology.

Hydrogel-encapsulation to enhance bacterial diagnosis of colon inflammation.

Bacteria can be genetically programmed to sense and report the presence of disease biomarkers in the gastrointestinal (GI) tract. However, diagnostic bacteria are typically delivered via oral administration of liquid cultures, resulting in poor survival and high dispersal in vivo. These limitations confound recovery and analysis of engineered bacteria from GI or stool samples. Here, we demonstrate that encapsulating bacteria inside of alginate core-shell particles enables robust survival, containment, and diagnostic function in vivo. We demonstrate these benefits by encapsulating a strain engineered to report the presence of the biomarker thiosulfate via fluorescent protein expression in order to diagnose dextran sodium sulfate-induced colitis in rats. Hydrogel-encapsulated bacteria engineered to sense and respond to physiological stimuli should enable minimally invasive monitoring of a wide range of diseases and have applications as next-generation smart therapeutics.

Meeting Measurement Precision Requirements for Effective Engineering of Genetic Regulatory Networks.

Reliable, predictable engineering of cellular behavior is one of the key goals of synthetic biology. As the field matures, biological engineers will become increasingly reliant on computer models that allow for the rapid exploration of design space prior to the more costly construction and characterization of candidate designs. The efficacy of such models, however, depends on the accuracy of their predictions, the precision of the measurements used to parametrize the models, and the tolerance of biological devices for imperfections in modeling and measurement. To better understand this relationship, we have derived an Engineering Error Inequality that provides a quantitative mathematical bound on the relationship between predictability of results, model accuracy, measurement precision, and device characteristics. We apply this relation to estimate measurement precision requirements for engineering genetic regulatory networks given current model and device characteristics, recommending a target standard deviation of 1.5-fold. We then compare these requirements with the results of an interlaboratory study to validate that these requirements can be met via flow cytometry with matched instrument channels and an independent calibrant. On the basis of these results, we recommend a set of best practices for quality control of flow cytometry data and discuss how these might be extended to other measurement modalities and applied to support further development of genetic regulatory network engineering.

Synthetic biology: engineering Escherichia coli to see light.

We have designed a bacterial system that is switched between different states by red light. The system consists of a synthetic sensor kinase that allows a lawn of bacteria to function as a biological film, such that the projection of a pattern of light on to the bacteria produces a high-definition (about 100 megapixels per square inch), two-dimensional chemical image. This spatial control of bacterial gene expression could be used to 'print' complex biological materials, for example, and to investigate signalling pathways through precise spatial and temporal control of their phosphorylation steps.

Bacterial two-component systems as sensors for synthetic biology applications.

Two-component systems (TCSs) are a ubiquitous family of signal transduction pathways that enable bacteria to sense and respond to diverse physical, chemical, and biological stimuli outside and inside the cell. Synthetic biologists have begun to repurpose TCSs for applications in optogenetics, materials science, gut microbiome engineering, and soil nutrient biosensing, among others. New engineering methods including genetic refactoring, DNA-binding domain swapping, detection threshold tuning, and phosphorylation cross-talk insulation are being used to increase the reliability of TCS sensor performance and tailor TCS signaling properties to the requirements of specific applications. There is now potential to combine these methods with large-scale gene synthesis and laboratory screening to discover the inputs sensed by many uncharacterized TCSs and develop a large new family of genetically-encoded sensors that respond to an unrivaled breadth of stimuli.

Independent control of mean and noise by convolution of gene expression distributions.

Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.

Synthetic biology open language visual (SBOL Visual) version 2.3.

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.3 of SBOL Visual, which builds on the prior SBOL Visual 2.2 in several ways. First, the specification now includes higher-level "interactions with interactions," such as an inducer molecule stimulating a repression interaction. Second, binding with a nucleic acid backbone can be shown by overlapping glyphs, as with other molecular complexes. Finally, a new "unspecified interaction" glyph is added for visualizing interactions whose nature is unknown, the "insulator" glyph is deprecated in favor of a new "inert DNA spacer" glyph, and the polypeptide region glyph is recommended for showing 2A sequences.