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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.

• 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.

Testing tomato gene expression with tagged nuclei and ribosomes and CRISPR/Cas9 genome editing shows conservation of SHORT-ROOT gene function. Abstract 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.

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.

Automated cell segmentation in time-lapse confocal images of growing Arabidopsis combined with ratiometric imaging of fluorescent gene expression reporters permits the correlation of cellular properties with gene expression in the growing plant. 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 .

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.

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.

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential use in a high school environment to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

Standardized type IIS DNA assembly methods are becoming essential for biological engineering and research. These methods are becoming widespread and more accessible due to the proposition of a ‘common syntax’ that enables higher interoperability between DNA libraries. Currently, Golden Gate (GG)-based assembly systems, originally implemented in host-specific vectors, are being made compatible with multiple organisms. We have recently developed the GG-based Loop assembly system for plants, which uses a small library and an intuitive strategy for hierarchical fabrication of large DNA constructs (>30 kb). Here, we describe ‘universal Loop’ (uLoop) assembly, a system based on Loop assembly for use in potentially any organism of choice. This design permits the use of a compact number of plasmids (two sets of four odd and even vectors), which are utilized repeatedly in alternating steps. The elements required for transformation/maintenance in target organisms are also assembled as standardized parts, enabling customization of host-specific plasmids. Decoupling of the Loop assembly logic from the host-specific propagation elements enables universal DNA assembly that retains high efficiency regardless of the final host. As a proof-of-concept, we show the engineering of multigene expression vectors in diatoms, yeast, plants and bacteria. These resources are available through the OpenMTA for unrestricted sharing and open access.

Abstract 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. Graphical Abstract