Spatial biology of Ising-like synthetic genetic networks.

BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS: Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS: Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.

Publisher Correction: Genetic tool development in marine protists: emerging model organisms for experimental cell biology.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic tool development in marine protists: emerging model organisms for experimental cell biology.

Diverse microbial ecosystems underpin life in the sea. Among these microbes are many unicellular eukaryotes that span the diversity of the eukaryotic tree of life. However, genetic tractability has been limited to a few species, which do not represent eukaryotic diversity or environmentally relevant taxa. Here, we report on the development of genetic tools in a range of protists primarily from marine environments. We present evidence for foreign DNA delivery and expression in 13 species never before transformed and for advancement of tools for eight other species, as well as potential reasons for why transformation of yet another 17 species tested was not achieved. Our resource in genetic manipulation will provide insights into the ancestral eukaryotic lifeforms, general eukaryote cell biology, protein diversification and the evolution of cellular pathways.

Loop assembly: a simple and open system for recursive fabrication of DNA circuits.

High-efficiency methods for DNA assembly have enabled the routine assembly of synthetic DNAs of increased size and complexity. However, these techniques require customization, elaborate vector sets or serial manipulations for the different stages of assembly. We have developed Loop assembly based on a recursive approach to DNA fabrication. The system makes use of two Type IIS restriction endonucleases and corresponding vector sets for efficient and parallel assembly of large DNA circuits. Standardized level 0 parts can be assembled into circuits containing 1, 4, 16 or more genes by looping between the two vector sets. The vectors also contain modular sites for hybrid assembly using sequence overlap methods. Loop assembly enables efficient and versatile DNA fabrication for plant transformation. We show the construction of plasmids up to 16 genes and 38 kb with high efficiency (> 80%). We have characterized Loop assembly on over 200 different DNA constructs and validated the fidelity of the method by high-throughput Illumina plasmid sequencing. Our method provides a simple generalized solution for DNA construction with standardized parts. The cloning system is provided under an OpenMTA license for unrestricted sharing and open access.

Orthogonal intercellular signaling for programmed spatial behavior.

Bidirectional intercellular signaling is an essential feature of multicellular organisms, and the engineering of complex biological systems will require multiple pathways for intercellular signaling with minimal crosstalk. Natural quorum-sensing systems provide components for cell communication, but their use is often constrained by signal crosstalk. We have established new orthogonal systems for cell-cell communication using acyl homoserine lactone signaling systems. Quantitative measurements in contexts of differing receiver protein expression allowed us to separate different types of crosstalk between 3-oxo-C6- and 3-oxo-C12-homoserine lactones, cognate receiver proteins, and DNA promoters. Mutating promoter sequences minimized interactions with heterologous receiver proteins. We used experimental data to parameterize a computational model for signal crosstalk and to estimate the effect of receiver protein levels on signal crosstalk. We used this model to predict optimal expression levels for receiver proteins, to create an effective two-channel cell communication device. Establishment of a novel spatial assay allowed measurement of interactions between geometrically constrained cell populations via these diffusible signals. We built relay devices capable of long-range signal propagation mediated by cycles of signal induction, communication and response by discrete cell populations. This work demonstrates the ability to systematically reduce crosstalk within intercellular signaling systems and to use these systems to engineer complex spatiotemporal patterning in cell populations.

Integrated genetic and computation methods for in planta cytometry.

We present the coupled use of specifically localized fluorescent gene markers and image processing for automated quantitative analysis of cell growth and genetic activity across living plant tissues. We used fluorescent protein markers to identify cells, create seeds and boundaries for the automatic segmentation of cell geometries and ratiometrically measure gene expression cell by cell in Arabidopsis thaliana.

Hairy root transformation using Agrobacterium rhizogenes as a tool for exploring cell type-specific gene expression and function using tomato as a model.

Agrobacterium rhizogenes (or Rhizobium rhizogenes) is able to transform plant genomes and induce the production of hairy roots. We describe the use of A. rhizogenes in tomato (Solanum spp.) to rapidly assess gene expression and function. Gene expression of reporters is indistinguishable in plants transformed by Agrobacterium tumefaciens as compared with A. rhizogenes. A root cell type- and tissue-specific promoter resource has been generated for domesticated and wild tomato (Solanum lycopersicum and Solanum pennellii, respectively) using these approaches. Imaging of tomato roots using A. rhizogenes coupled with laser scanning confocal microscopy is facilitated by the use of a membrane-tagged protein fused to a red fluorescent protein marker present in binary vectors. Tomato-optimized isolation of nuclei tagged in specific cell types and translating ribosome affinity purification binary vectors were generated and used to monitor associated messenger RNA abundance or chromatin modification. Finally, transcriptional reporters, translational reporters, and clustered regularly interspaced short palindromic repeats-associated nuclease9 genome editing demonstrate that SHORT-ROOT and SCARECROW gene function is conserved between Arabidopsis (Arabidopsis thaliana) and tomato.

Genetic Network Design Automation with LOICA.

Genetic design automation (GDA) is the use of computer-aided design (CAD) in designing genetic networks. GDA tools are necessary to create more complex synthetic genetic networks in a high-throughput fashion. At the core of these tools is the abstraction of a hierarchy of standardized components. The components' input, output, and interactions must be captured and parametrized from relevant experimental data. Simulations of genetic networks should use those parameters and include the experimental context to be compared with the experimental results.This chapter introduces Logical Operators for Integrated Cell Algorithms (LOICA), a Python package used for designing, modeling, and characterizing genetic networks using a simple object-oriented design abstraction. LOICA represents different biological and experimental components as classes that interact to generate models. These models can be parametrized by direct connection to the Flapjack experimental data management platform to characterize abstracted components with experimental data. The models can be simulated using stochastic simulation algorithms or ordinary differential equations with varying noise levels. The simulated data can be managed and published using Flapjack alongside experimental data for comparison. LOICA genetic network designs can be represented as graphs and plotted as networks for visual inspection and serialized as Python objects or in the Synthetic Biology Open Language (SBOL) format for sharing and use in other designs.

Flapjack: Data Management and Analysis for Genetic Circuit Characterization.

Flapjack presents a valuable solution for addressing challenges in the Design, Build, Test, Learn (DBTL) cycle of engineering synthetic genetic circuits. This platform provides a comprehensive suite of features for managing, analyzing, and visualizing kinetic gene expression data and associated metadata. By utilizing the Flapjack platform, researchers can effectively integrate the test phase with the build and learn phases, facilitating the characterization and optimization of genetic circuits. With its user-friendly interface and compatibility with external software, the Flapjack platform offers a practical tool for advancing synthetic biology research.This chapter provides an overview of the data model employed in Flapjack and its hierarchical structure, which aligns with the typical steps involved in conducting experiments and facilitating intuitive data management for users. Additionally, this chapter offers a detailed description of the user interface, guiding readers through accessing Flapjack, navigating its sections, performing essential tasks such as uploading data and creating plots, and accessing the platform through the pyFlapjack Python package.

An Open One-Step RT-qPCR for SARS-CoV-2 detection.

The COVID-19 pandemic has resulted in millions of deaths globally, and while several diagnostic systems were proposed, real-time reverse transcription polymerase chain reaction (RT-PCR) remains the gold standard. However, diagnostic reagents, including enzymes used in RT-PCR, are subject to centralized production models and intellectual property restrictions, which present a challenge for less developed countries. With the aim of generating a standardized One-Step open RT-qPCR protocol to detect SARS-CoV-2 RNA in clinical samples, we purified and tested recombinant enzymes and a non-proprietary buffer. The protocol utilized M-MLV RT and Taq DNA pol enzymes to perform a Taqman probe-based assay. Synthetic RNA samples were used to validate the One-Step RT-qPCR components, demonstrating sensitivity comparable to a commercial kit routinely employed in clinical settings for patient diagnosis. Further evaluation on 40 clinical samples (20 positive and 20 negative) confirmed its comparable diagnostic accuracy. This study represents a proof of concept for an open approach to developing diagnostic kits for viral infections and diseases, which could provide a cost-effective and accessible solution for less developed countries.

Synthetic Biology: opportunities for Chilean bioindustry and education.

In an age of pressing challenges for sustainable production of energy and food, the new field of Synthetic Biology has emerged as a promising approach to engineer biological systems. Synthetic Biology is formulating the design principles to engineer affordable, scalable, predictable and robust functions in biological systems. In addition to efficient transfer of evolved traits from one organism to another, Synthetic Biology offers a new and radical approach to bottom-up engineering of sensors, actuators, dynamical controllers and the biological chassis they are embedded in. Because it abstracts much of the mechanistic details underlying biological component behavior, Synthetic Biology methods and resources can be readily used by interdisciplinary teams to tackle complex problems. In addition, the advent of robust new methods for the assembly of large genetic circuits enables teaching Biology and Bioengineering in a learning-by-making fashion for diverse backgrounds at the graduate, undergraduate and high school levels. Synthetic Biology offers unique opportunities to empower interdisciplinary training, research and industrial development in Chile for a technology that promises a significant role in this century's economy.

An Open One-Step RT-qPCR for SARS-CoV-2 detection.

The COVID-19 pandemic has resulted in millions of deaths globally, and while several diagnostic systems were proposed, real-time reverse transcription polymerase chain reaction (RT-PCR) remains the gold standard. However, diagnostic reagents, including enzymes used in RT-PCR, are subject to centralized production models and intellectual property restrictions, which present a challenge for less developed countries. With the aim of generating a standardized One-Step open RT-qPCR protocol to detect SARS-CoV-2 RNA in clinical samples, we purified and tested recombinant enzymes and a non-proprietary buffer. The protocol utilized M-MLV RT and Taq DNA pol enzymes to perform a Taqman probe-based assay. Synthetic RNA samples were used to validate the One-Step RT-qPCR components, and the kit showed comparable sensitivity to approved commercial kits. The One-Step RT-qPCR was then tested on clinical samples and demonstrated similar performance to commercial kits in terms of positive and negative calls. This study represents a proof of concept for an open approach to developing diagnostic kits for viral infections and diseases, which could provide a cost-effective and accessible solution for less developed countries.

High-resolution live imaging of plant growth in near physiological bright conditions using light sheet fluorescence microscopy.

Most plant growth occurs post-embryonically and is characterized by the constant and iterative formation of new organs. Non-invasive time-resolved imaging of intact, fully functional organisms allows studies of the dynamics involved in shaping complex organisms. Conventional and confocal fluorescence microscopy suffer from limitations when whole living organisms are imaged at single-cell resolution. We applied light sheet-based fluorescence microscopy to overcome these limitations and study the dynamics of plant growth. We designed a special imaging chamber in which the plant is maintained vertically under controlled illumination with its leaves in the air and its root in the medium. We show that minimally invasive, multi-color, three-dimensional imaging of live Arabidopsis thaliana samples can be achieved at organ, cellular and subcellular scales over periods of time ranging from seconds to days with minimal damage to the sample. We illustrate the capabilities of the method by recording the growth of primary root tips and lateral root primordia over several hours. This allowed us to quantify the contribution of cell elongation to the early morphogenesis of lateral root primordia and uncover the diurnal growth rhythm of lateral roots. We demonstrate the applicability of our approach at varying spatial and temporal scales by following the division of plant cells as well as the movement of single endosomes in live growing root samples. This multi-dimensional approach will have an important impact on plant developmental and cell biology and paves the way to a truly quantitative description of growth processes at several scales.

A molecular framework for the inhibition of Arabidopsis root growth in response to boron toxicity.

Boron is an essential micronutrient for plants and is taken up in the form of boric acid (BA). Despite this, a high BA concentration is toxic for the plants, inhibiting root growth and is thus a significant problem in semi-arid areas in the world. In this work, we report the molecular basis for the inhibition of root growth caused by boron. We show that application of BA reduces the size of root meristems, correlating with the inhibition of root growth. The decrease in meristem size is caused by a reduction of cell division. Mitotic cell number significantly decreases and the expression level of key core cell cycle regulators is modulated. The modulation of the cell cycle does not appear to act through cytokinin and auxin signalling. A global expression analysis reveals that boron toxicity induces the expression of genes related with abscisic acid (ABA) signalling, ABA response and cell wall modifications, and represses genes that code for water transporters. These results suggest that boron toxicity produces a reduction of water and BA uptake, triggering a hydric stress response that produces root growth inhibition.

Accurate characterization of dynamic microbial gene expression and growth rate profiles.

Genetic circuits are subject to variability due to cellular and compositional contexts. Cells face changing internal states and environments, the cellular context, to which they sense and respond by changing their gene expression and growth rates. Furthermore, each gene in a genetic circuit operates in a compositional context of genes which may interact with each other and the host cell in complex ways. The context of genetic circuits can, therefore, change gene expression and growth rates, and measuring their dynamics is essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of microbial gene expression and growth rate profiles from typical noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for the estimation of dynamic microbial gene expression rates and growth rates from noisy measurement data. Compared to the current state-of-the-art, our method significantly reduced the mean squared error of reconstructions from simulated data of growth and gene expression rates, improving the estimation of timing and magnitude of relevant shapes of profiles. We applied our method to characterize a triple-reporter plasmid library combining multiple transcription units in different compositional and cellular contexts in Escherichia coli. Our analysis reveals cellular and compositional context effects on microbial growth and gene expression rate dynamics and suggests a method for the dynamic ratiometric characterization of constitutive promoters relative to an in vivo reference.

Constructing Cell-Free Expression Systems for Low-Cost Access.

Cell-free systems for gene expression have gained attention as platforms for the facile study of genetic circuits and as highly effective tools for teaching. Despite recent progress, the technology remains inaccessible for many in low- and middle-income countries due to the expensive reagents required for its manufacturing, as well as specialized equipment required for distribution and storage. To address these challenges, we deconstructed processes required for cell-free mixture preparation and developed a set of alternative low-cost strategies for easy production and sharing of extracts. First, we explored the stability of cell-free reactions dried through a low-cost device based on silica beads, as an alternative to commercial automated freeze dryers. Second, we report the positive effect of lactose as an additive for increasing protein synthesis in maltodextrin-based cell-free reactions using either circular or linear DNA templates. The modifications were used to produce active amounts of two high-value reagents: the isothermal polymerase Bst and the restriction enzyme BsaI. Third, we demonstrated the endogenous regeneration of nucleoside triphosphates and synthesis of pyruvate in cell-free systems (CFSs) based on phosphoenol pyruvate (PEP) and maltodextrin (MDX). We exploited this novel finding to demonstrate the use of a cell-free mixture completely free of any exogenous nucleotide triphosphates (NTPs) to generate high yields of sfGFP expression. Together, these modifications can produce desiccated extracts that are 203-424-fold cheaper than commercial versions. These improvements will facilitate wider use of CFS for research and education purposes.

Decentralizing Cell-Free RNA Sensing With the Use of Low-Cost Cell Extracts.

Cell-free gene expression systems have emerged as a promising platform for field-deployed biosensing and diagnostics. When combined with programmable toehold switch-based RNA sensors, these systems can be used to detect arbitrary RNAs and freeze-dried for room temperature transport to the point-of-need. These sensors, however, have been mainly implemented using reconstituted PURE cell-free protein expression systems that are difficult to source in the Global South due to their high commercial cost and cold-chain shipping requirements. Based on preliminary demonstrations of toehold sensors working on lysates, we describe the fast prototyping of RNA toehold switch-based sensors that can be produced locally and reduce the cost of sensors by two orders of magnitude. We demonstrate that these in-house cell lysates provide sensor performance comparable to commercial PURE cell-free systems. We further optimize these lysates with a CRISPRi strategy to enhance the stability of linear DNAs by knocking-down genes responsible for linear DNA degradation. This enables the direct use of PCR products for fast screening of new designs. As a proof-of-concept, we develop novel toehold sensors for the plant pathogen Potato Virus Y (PVY), which dramatically reduces the yield of this important staple crop. The local implementation of low-cost cell-free toehold sensors could enable biosensing capacity at the regional level and lead to more decentralized models for global surveillance of infectious disease.

Homebrew reagents for low cost RT-LAMP.

RT-LAMP (reverse transcription - Loop-mediated isothermal amplification) has gained popularity for the detection of SARS-CoV-2. The high specificity, sensitivity, simple protocols and potential to deliver results without the use of expensive equipment has made it an attractive alternative to RT-PCR. However, the high cost per reaction, the centralized manufacturing of required reagents and their distribution under cold chain shipping limits RT-LAMP's applicability in low-income settings. The preparation of assays using homebrew enzymes and buffers has emerged worldwide as a response to these limitations and potential shortages. Here, we describe the production of Moloney murine leukemia virus (M-MLV) Reverse Transcriptase and BstLF DNA polymerase for the local implementation of RT-LAMP reactions at low cost. These reagents compared favorably to commercial kits and optimum concentrations were defined in order to reduce time to threshold, increase ON/OFF range and minimize enzyme quantities per reaction. As a validation, we tested the performance of these reagents in the detection of SARS-CoV-2 from RNA extracted from clinical nasopharyngeal samples, obtaining high agreement between RT-LAMP and RT-PCR clinical results. The in-house preparation of these reactions results in an order of magnitude reduction in costs, and thus we provide protocols and DNA to enable the replication of these tests at other locations. These results contribute to the global effort of developing open and low cost diagnostics that enable technological autonomy and distributed capacities in viral surveillance.

Accessible LAMP-Enabled Rapid Test (ALERT) for Detecting SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted bottlenecks in large-scale, frequent testing of populations for infections. Polymerase chain reaction (PCR)-based diagnostic tests are expensive, reliant on centralized labs, can take days to deliver results, and are prone to backlogs and supply shortages. Antigen tests that bind and detect the surface proteins of a virus are rapid and scalable but suffer from high false negative rates. To address this problem, an inexpensive, simple, and robust 60-minute do-it-yourself (DIY) workflow to detect viral RNA from nasal swabs or saliva with high sensitivity (0.1 to 2 viral particles/µL) and specificity (>97% true negative rate) utilizing reverse transcription loop-mediated isothermal amplification (RT-LAMP) was developed. ALERT (Accessible LAMP-Enabled Rapid Test) incorporates the following features: (1) increased shelf-life and ambient temperature storage, compared to liquid reaction mixes, by using wax layers to isolate enzymes from other reagents; (2) improved specificity compared to other LAMP end-point reporting methods, by using sequence-specific QUASR (quenching of unincorporated amplification signal reporters); (3) increased sensitivity, compared to methods without purification through use of a magnetic wand to enable pipette-free concentration of sample RNA and cell debris removal; (4) quality control with a nasopharyngeal-specific mRNA target; and (5) co-detection of other respiratory viruses, such as influenza B, by multiplexing QUASR-modified RT-LAMP primer sets. The flexible nature of the ALERT workflow allows easy, at-home and point-of-care testing for individuals and higher-throughput processing for labs and hospitals. With minimal effort, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific primer sets can be swapped out for other targets to repurpose ALERT to detect other viruses, microorganisms, or nucleic acid-based markers.

Homebrew reagents for low-cost RT-LAMP.

Reverse transcription-loop-mediated isothermal amplification (RT-LAMP) has gained popularity for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The high specificity, sensitivity, simple protocols, and potential to deliver results without the use of expensive equipment has made it an attractive alternative to RT-PCR. However, the high cost per reaction, the centralized manufacturing of required reagents, and their distribution under cold chain shipping limit RT-LAMP's applicability in low-income settings. The preparation of assays using homebrew enzymes and buffers has emerged worldwide as a response to these limitations and potential shortages. Here, we describe the production of Moloney murine leukemia virus reverse transcriptase and BstLF DNA polymerase for the local implementation of RT-LAMP reactions at low cost. These reagents compared favorably to commercial kits, and optimum concentrations were defined in order to reduce time to threshold, increase ON/OFF range, and minimize enzyme quantities per reaction. As a validation, we tested the performance of these reagents in the detection of SARS-CoV-2 from RNA extracted from clinical nasopharyngeal samples, obtaining high agreement between RT-LAMP and RT-PCR clinical results. The in-house preparation of these reactions results in an order of magnitude reduction in costs; thus, we provide protocols and DNA to enable the replication of these tests at other locations. These results contribute to the global effort of developing open and low-cost diagnostics that enable technological autonomy and distributed capacities in viral surveillance.