Rational programming of history-dependent logic in cellular populations

Biocomputing in plants, from proof of concept to application

In response to the challenges of climate change and the transition toward sustainability, synthetic biology offers innovative solutions. Most current plant synthetic biology applications rely on the constitutive expression of enzymes and regulators. To engineer plant phenotypes tuneable to environmental conditions and plant cellular states, the integration of multiple signals in synthetic circuits is required. While most circuits are developed in model organisms, numerous tools were recently developed to implement biocomputation in plant synthetic circuits. I presented in this review the tools and design methods for logic circuit implementation in plants. I highlighted recent and potential applications of those circuits to understand and engineer plant interaction with the environment, development, and metabolic pathways.

Engineering intelligent chassis cells via recombinase-based MEMORY circuits

Synthetic biologists seek to engineer intelligent living systems capable of decision-making, communication, and memory. Separate technologies exist for each tenet of intelligence; however, the unification of all three properties in a living system has not been achieved. Here, we engineer completely intelligent Escherichia coli strains that harbor six orthogonal and inducible genome-integrated recombinases, forming Molecularly Encoded Memory via an Orthogonal Recombinase arraY (MEMORY). MEMORY chassis cells facilitate intelligence via the discrete multi-input regulation of recombinase functions enabling inheritable DNA inversions, deletions, and genomic insertions. MEMORY cells can achieve programmable and permanent gain (or loss) of functions extrachromosomally or from a specific genomic locus, without the loss or modification of the MEMORY platform - enabling the sequential programming and reprogramming of DNA circuits within the cell. We demonstrate all three tenets of intelligence via a probiotic (Nissle 1917) MEMORY strain capable of information exchange with the gastrointestinal commensal Bacteroides thetaiotaomicron.

Customizing cellular signal processing by synthetic multi-level regulatory circuits

As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.

Next generation synthetic memory via intercepting recombinase function

Here we present a technology to facilitate synthetic memory in a living system via repurposing Transcriptional Programming (i.e., our decision-making technology) parts, to regulate (intercept) recombinase function post-translation. We show that interception synthetic memory can facilitate programmable loss-of-function via site-specific deletion, programmable gain-of-function by way of site-specific inversion, and synthetic memory operations with nested Boolean logical operations. We can expand interception synthetic memory capacity more than 5-fold for a single recombinase, with reconfiguration specificity for multiple sites in parallel. Interception synthetic memory is ~10-times faster than previous generations of recombinase-based memory. We posit that the faster recombination speed of our next-generation memory technology is due to the post-translational regulation of recombinase function. This iteration of synthetic memory is complementary to decision-making via Transcriptional Programming - thus can be used to develop intelligent synthetic biological systems for myriad applications.

An integrase toolbox to record gene-expression during plant development

There are many open questions about the mechanisms that coordinate the dynamic, multicellular behaviors required for organogenesis. Synthetic circuits that can record in vivo signaling networks have been critical in elucidating animal development. Here, we report on the transfer of this technology to plants using orthogonal serine integrases to mediate site-specific and irreversible DNA recombination visualized by switching between fluorescent reporters. When combined with promoters expressed during lateral root initiation, integrases amplify reporter signal and permanently mark all descendants. In addition, we present a suite of methods to tune the threshold for integrase switching, including: RNA/protein degradation tags, a nuclear localization signal, and a split-intein system. These tools improve the robustness of integrase-mediated switching with different promoters and the stability of switching behavior over multiple generations. Although each promoter requires tuning for optimal performance, this integrase toolbox can be used to build history-dependent circuits to decode the order of expression during organogenesis in many contexts.

A DNA Finite-State Machine Based on the Programmable Allosteric Strategy of DNAzyme

Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology.

Computational Methods for the Design of Recombinase Logic Circuits with Adaptable Circuit Specifications

Synthetic biology aims at engineering new biological systems and functions that can be used to provide new technological solutions to worldwide challenges. Detection and processing of multiple signals are crucial for many synthetic biology applications. A variety of logic circuits operating in living cells have been implemented. One particular class of logic circuits uses site-specific recombinases mediating specific DNA inversion or excision. Recombinase logic offers many interesting features, including single-layer architectures, memory, low metabolic footprint, and portability in many species. Here, we present two automated design strategies for both Boolean and history-dependent recombinase-based logic circuits. One approach is based on the distribution of computation within multicellular consortia, and the other is a single-cell design. Both are complementary and adapted for non-expert users via a web design interface, called CALIN and RECOMBINATOR, for multicellular and single-cell design strategies, respectively. In this book chapter, we are guiding the reader step by step through recombinase logic circuit design, from selecting the design strategy fitting to their final system of interest to obtaining the final design using one of our design web interfaces.

Synthetic memory circuits for stable cell reprogramming in plants

Plant biotechnology predominantly relies on a restricted set of genetic parts with limited capability to customize spatiotemporal and conditional expression patterns. Synthetic gene circuits have the potential to integrate multiple customizable input signals through a processing unit constructed from biological parts to produce a predictable and programmable output. Here we present a suite of functional recombinase-based gene circuits for use in plants. We first established a range of key gene circuit components compatible with plant cell functionality. We then used these to develop a range of operational logic gates using the identify function (activation) and negation function (repression) in Arabidopsis protoplasts and in vivo, demonstrating their utility for programmable manipulation of transcriptional activity in a complex multicellular organism. Specifically, using recombinases and plant control elements, we activated transgenes in YES, OR and AND gates and repressed them in NOT, NOR and NAND gates; we also implemented the A NIMPLY B gate that combines activation and repression. Through use of genetic recombination, these circuits create stable long-term changes in expression and recording of past stimuli. This highly compact programmable gene circuit platform provides new capabilities for engineering sophisticated transcriptional programs and previously unrealized traits into plants.

A rapid and standardized workflow for functional assessment of bacterial biosensors in fecal samples

Gut metabolites are pivotal mediators of host-microbiome interactions and provide an important window on human physiology and disease. However, current methods to monitor gut metabolites rely on heavy and expensive technologies such as liquid chromatography-mass spectrometry (LC-MS). In that context, robust, fast, field-deployable, and cost-effective strategies for monitoring fecal metabolites would support large-scale functional studies and routine monitoring of metabolites biomarkers associated with pathological conditions. Living cells are an attractive option to engineer biosensors due to their ability to detect and process many environmental signals and their self-replicating nature. Here we optimized a workflow for feces processing that supports metabolite detection using bacterial biosensors. We show that simple centrifugation and filtration steps remove host microbes and support reproducible preparation of a physiological-derived media retaining important characteristics of human feces, such as matrix effects and endogenous metabolites. We measure the performance of bacterial biosensors for benzoate, lactate, anhydrotetracycline, and bile acids, and find that they are highly sensitive to fecal matrices. However, encapsulating the bacteria in hydrogel helps reduce this inhibitory effect. Sensitivity to matrix effects is biosensor-dependent but also varies between individuals, highlighting the need for case-by-case optimization for biosensors’ operation in feces. Finally, by detecting endogenous bile acids, we demonstrate that bacterial biosensors could be used for future metabolite monitoring in feces. This work lays the foundation for the optimization and use of bacterial biosensors for fecal metabolites monitoring. In the future, our method could also allow rapid pre-prototyping of engineered bacteria designed to operate in the gut, with applications to in situ diagnostics and therapeutics.

DNA nanotechnology-empowered finite state machines

A finite state machine (FSM, or automaton) is an abstract machine that can switch among a finite number of states in response to temporally ordered inputs, which allows storage and processing of information in an order-sensitive manner. In recent decades, DNA molecules have been actively exploited to develop information storage and nanoengineering materials, which hold great promise for smart nanodevices and nanorobotics under the framework of FSM. In this review, we summarize recent progress in utilizing DNA self-assembly and DNA nanostructures to implement FSMs. We describe basic principles for representative DNA FSM prototypes and highlight their advantages and potential in diverse applications. The challenges in this field and future directions have also been discussed.

A localized DNA finite-state machine with temporal resolution

The identity and timing of environmental stimulus play a pivotal role in living organisms in programming their signaling networks and developing specific phenotypes. The ability to unveil history-dependent signals will advance our understanding of temporally regulated biological processes. Here, we have developed a two-input, five-state DNA finite-state machine (FSM) to sense and record the temporally ordered inputs. The spatial organization of the processing units on DNA origami enables facile modulation of the energy landscape of DNA strand displacement reactions, allowing precise control of the reactions along predefined paths for different input orders. The use of spatial constraints brings about a simple, modular design for the FSM with a minimum set of orthogonal components and confers minimized leaky reactions and fast kinetics. The FSM demonstrates the capability of sensing the temporal orders of two microRNAs, highlighting its potential for temporally resolved biosensing and smart therapeutics.

SYMBIOSIS: synthetic manipulable biobricks via orthogonal serine integrase systems

Serine integrases are emerging as one of the most powerful biological tools for synthetic biology. They have been widely used across genome engineering and genetic circuit design. However, developing serine integrase-based tools for directly/precisely manipulating synthetic biobricks is still missing. Here, we report SYMBIOSIS, a versatile method that can robustly manipulate DNA parts in vivo and in vitro. First, we propose a 'keys match locks' model to demonstrate that three orthogonal serine integrases are able to irreversibly and stably switch on seven synthetic biobricks with high accuracy in vivo. Then, we demonstrate that purified integrases can facilitate the assembly of 'donor' and 'acceptor' plasmids in vitro to construct composite plasmids. Finally, we use SYMBIOSIS to assemble different chromoprotein genes and create novel colored Escherichia coli. We anticipate that our SYMBIOSIS strategy will accelerate synthetic biobrick manipulation, genetic circuit design and multiple plasmid assembly for synthetic biology with broad potential applications.

Future Challenges in Plant Systems Biology

Plant systems biology is currently facing several important challenges, whose nature depend on the considered frame of reference and associated scale. This review covers some of the issues associated respectively with the molecular, tissue, and whole-plant scales, as well as discusses the potential for latest advances in synthetic biology and machine-learning methods to be of use in the future of plant systems biology.

Decoding and recoding plant development

The development of multicellular organisms has been studied for centuries, yet many critical events and mechanisms of regulation remain challenging to observe directly. Early research focused on detailed observational and comparative studies. Molecular biology has generated insights into regulatory mechanisms, but only for a limited number of species. Now, synthetic biology is bringing these two approaches together, and by adding the possibility of sculpting novel morphologies, opening another path to understanding biology. Here, we review a variety of recently invented techniques that use CRISPR/Cas9 and phage integrases to trace the differentiation of cells over various timescales, as well as to decode the molecular states of cells in high spatiotemporal resolution. Most of these tools have been implemented in animals. The time is ripe for plant biologists to adopt and expand these approaches. Here, we describe how these tools could be used to monitor development in diverse plant species, as well as how they could guide efforts to recode programs of interest.

Synthetic biology in the clinic: engineering vaccines, diagnostics, and therapeutics

Synthetic biology is a design-driven discipline centered on engineering novel biological functions through the discovery, characterization, and repurposing of molecular parts. Several synthetic biological solutions to critical biomedical problems are on the verge of widespread adoption and demonstrate the burgeoning maturation of the field. Here, we highlight applications of synthetic biology in vaccine development, molecular diagnostics, and cell-based therapeutics, emphasizing technologies approved for clinical use or in active clinical trials. We conclude by drawing attention to recent innovations in synthetic biology that are likely to have a significant impact on future applications in biomedicine.