RNA-based gene circuits for cell regulation

Orthogonal inducible control of Cas13 circuits enables programmable RNA regulation in mammalian cells

RNA plays an indispensable role in mammalian cell functions. Cas13, a class of RNA-guided ribonuclease, is a flexible tool for modifying and regulating coding and non-coding RNAs, with enormous potential for creating new cell functions. However, the lack of control over Cas13 activity has limited its cell engineering capability. Here, we present the CRISTAL (Control of RNA with Inducible SpliT CAs13 Orthologs and Exogenous Ligands) platform. CRISTAL is powered by a collection (10 total) of orthogonal split inducible Cas13 effectors that can be turned ON or OFF via small molecules in multiple cell types, providing precise temporal control. Also, we engineer Cas13 logic circuits that can respond to endogenous signaling and exogenous small molecule inputs. Furthermore, the orthogonality, low leakiness, and high dynamic range of our inducible Cas13d and Cas13b enable the design and construction of a robust incoherent feedforward loop, leading to near-perfect and tunable adaptation response. Finally, using our inducible Cas13 effectors, we achieve simultaneous multiplexed control of multiple genes in vitro and in mice. Together, our CRISTAL design represents a powerful platform for precisely regulating RNA dynamics to advance cell engineering and elucidate RNA biology.

Blood-Glucose-Powered Metabolic Fuel Cell for Self-Sufficient Bioelectronics

Currently available bioelectronic devices consume too much power to be continuously operated on rechargeable batteries, and are often powered wirelessly, with attendant issues regarding reliability, convenience, and mobility. Thus, the availability of a robust, self-sufficient, implantable electrical power generator that works under physiological conditions would be transformative for many applications, from driving bioelectronic implants and prostheses to programing cellular behavior and patients' metabolism. Here, capitalizing on a new copper-containing, conductively tuned 3D carbon nanotube composite, an implantable blood-glucose-powered metabolic fuel cell is designed that continuously monitors blood-glucose levels, converts excess glucose into electrical power during hyperglycemia, and produces sufficient energy (0.7 mW cm^-2 , 0.9 V, 50 mm glucose) to drive opto- and electro-genetic regulation of vesicular insulin release from engineered beta cells. It is shown that this integration of blood-glucose monitoring with elimination of excessive blood glucose by combined electro-metabolic conversion and insulin-release-mediated cellular consumption enables the metabolic fuel cell to restore blood-glucose homeostasis in an automatic, self-sufficient, and closed-loop manner in an experimental model of type-1 diabetes.

Orthogonal inducible control of Cas13 circuits enables programmable RNA regulation in mammalian cells

RNA plays an indispensable role in mammalian cell functions. Cas13, a class of RNA-guided ribonuclease, is a flexible tool for modifying and regulating coding and non-coding RNAs, with enormous potential for creating new cell functions. However, the lack of control over Cas13 activity has limited its cell engineering capability. Here, we present the CRISTAL ( C ontrol of R NA with Inducible S pli T C A s13 Orthologs and Exogenous L igands) platform. CRISTAL is powered by a collection (10 total) of orthogonal split inducible Cas13s that can be turned ON or OFF via small molecules in multiple cell types, providing precise temporal control. Also, we engineered Cas13 logic circuits that can respond to endogenous signaling and exogenous small molecule inputs. Furthermore, the orthogonality, low leakiness, and high dynamic range of our inducible Cas13d and Cas13b enable the design and construction of a robust incoherent feedforward loop, leading to near-perfect and tunable adaptation response. Finally, using our inducible Cas13s, we achieve simultaneous multiplexed control of multiple genes in vitro and in mice. Together, our CRISTAL design represents a powerful platform for precisely regulating RNA dynamics to advance cell engineering and elucidate RNA biology.

Synthetic Biology Meets Machine Learning

This chapter outlines the myriad applications of machine learning (ML) in synthetic biology, specifically in engineering cell and protein activity, and metabolic pathways. Though by no means comprehensive, the chapter highlights several prominent computational tools applied in the field and their potential use cases. The examples detailed reinforce how ML algorithms can enhance synthetic biology research by providing data-driven insights into the behavior of living systems, even without detailed knowledge of their underlying mechanisms. By doing so, ML promises to increase the efficiency of research projects by modeling hypotheses in silico that can then be tested through experiments. While challenges related to training dataset generation and computational costs remain, ongoing improvements in ML tools are paving the way for smarter and more streamlined synthetic biology workflows that can be readily employed to address grand challenges across manufacturing, medicine, engineering, agriculture, and beyond.

Xeno-free induced pluripotent stem cell-derived neural progenitor cells for in vivo applications

BACKGROUND

Currently, there is no regenerative therapy for patients with neurological and neurodegenerative disorders. Cell-therapies have emerged as a potential treatment for numerous brain diseases. Despite recent advances in stem cell technology, major concerns have been raised regarding the feasibility and safety of cell therapies for clinical applications.

METHODS

We generated good manufacturing practice (GMP)-compatible neural progenitor cells (NPCs) from transgene- and xeno-free induced pluripotent stem cells (iPSCs) that can be smoothly adapted for clinical applications. NPCs were characterized in vitro for their differentiation potential and in vivo after transplantation into wild type as well as genetically immunosuppressed mice.

RESULTS

Generated NPCs had a stable gene-expression over at least 15 passages and could be scaled for up to 1018 cells per initially seeded 106 cells. After withdrawal of growth factors in vitro, cells adapted a neural fate and mainly differentiated into active neurons. To ensure a pure NPC population for in vivo applications, we reduced the risk of iPSC contamination by applying micro RNA-switch technology as a safety checkpoint. Using lentiviral transduction with a fluorescent and bioluminescent dual-reporter construct, combined with non-invasive in vivo bioluminescent imaging, we longitudinally tracked the grafted cells in healthy wild-type and genetically immunosuppressed mice as well as in a mouse model of ischemic stroke. Long term in-depth characterization revealed that transplanted NPCs have the capability to survive and spontaneously differentiate into functional and mature neurons throughout a time course of a month, while no residual pluripotent cells were detectable.

CONCLUSION

We describe the generation of transgene- and xeno-free NPCs. This simple differentiation protocol combined with the ability of in vivo cell tracking presents a valuable tool to develop safe and effective cell therapies for various brain injuries.

From Endogenous to Synthetic microRNA-Mediated Regulatory Circuits: An Overview

MicroRNAs are short non-coding RNAs that are evolutionarily conserved and are pivotal post-transcriptional mediators of gene regulation. Together with transcription factors and epigenetic regulators, they form a highly interconnected network whose building blocks can be classified depending on the number of molecular species involved and the type of interactions amongst them. Depending on their topology, these molecular circuits may carry out specific functions that years of studies have related to the processing of gene expression noise. In this review, we first present the different over-represented network motifs involving microRNAs and their specific role in implementing relevant biological functions, reviewing both theoretical and experimental studies. We then illustrate the recent advances in synthetic biology, such as the construction of artificially synthesised circuits, which provide a controlled tool to test experimentally the possible microRNA regulatory tasks and constitute a starting point for clinical applications.

Biomaterial-based delivery systems of nucleic acid for regenerative research and regenerative therapy

Regenerative medicine is a new and promising medical method aiming at treating patients with defective or dysfunctional tissues by maintaining or enhancing the biological activity of cells. The development of biomaterial-based technologies, such as cell scaffolds and carriers for drug delivery system, are highly required to promote the regenerative research and regenerative therapy. Nucleic acids are one of the most feasible factors to efficiently modify the biological activity of cells. The effective and stable delivery of nucleic acids into cells is highly required to succeed in the modification. Biomaterials-based non-viral carriers or biological carriers, like exosomes, play an important role in the efficient delivery of nucleic acids. This review introduces the examples of regenerative research and regenerative therapy based on the delivery of nucleic acids with biomaterials technologies and emphasizes their importance to accomplish regenerative medicine.

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Modifying the activity of cells is important for regenerative medicine.

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Various nucleic acids regulate gene expression to modify the activity of cells.

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Intracellular delivery system is vital to the nucleic acids-based modification.

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Biomaterials are useful for the intracellular delivery of nucleic acids.

Evolving methods for rational de novo design of functional RNA molecules

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.

Advances in engineered trans-acting regulatory RNAs and their application in bacterial genome engineering

Small noncoding RNAs, a large class of ancient posttranscriptional regulators, are increasingly recognized and utilized as key modulators of gene expression in a broad range of microorganisms. Owing to their small molecular size and the central role of Watson-Crick base pairing in defining their interactions, structure and function, numerous diverse types of trans-acting RNA regulators that are functional at the DNA, mRNA and protein levels have been experimentally characterized. It has become increasingly clear that most small RNAs play critical regulatory roles in many processes and are, therefore, considered to be powerful tools for genetic engineering and synthetic biology. The trans-acting regulatory RNAs accelerate this ability to establish potential framework for genetic engineering and genome-scale engineering, which allows RNA structure characterization, easier to design and model compared to DNA or protein-based systems. In this review, we summarize recent advances in engineered trans-acting regulatory RNAs that are used in bacterial genome-scale engineering and in novel cellular capabilities as well as their implementation in wide range of biotechnological, biological and medical applications.

Designed and Evolved Nucleic Acid Nanotechnology: Contrast and Complementarity

In this review, we explore progress on DNA aptamers (evolved DNA), DNA circuits (designed DNA), and the newest projects that integrate both. Designed DNA nanotechnology includes static nanostructures, dynamic nanodevices, and reaction networks (sometimes called DNA circuits). DNA circuits are dynamic DNA reactions that perform computations and sequence-specific amplification. Directed evolution can be used to produce DNA that can recognize specific targets. Aptamers are evolved nucleic acids; they are produced artificially with an in vitro selection process. DNA aptamers are molecular recognition elements made of single-stranded DNA (ssDNA) with the potential to interact with proteins, small molecules, viruses, and even cells. Designed molecular structures can incorporate aptamers for applications with immediate practical impact.

Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.

Increasing the length of poly-pyrimidine bulges broadens RNA conformational ensembles with minimal impact on stacking energetics

Helical elements separated by bulges frequently undergo transitions between unstacked and coaxially stacked conformations during the folding and function of noncoding RNAs. Here, we examine the dynamic properties of poly-pyrimidine bulges of varying length (n = 1-4, 7) across a range of Mg²⁺ concentrations using HIV-1 TAR RNA as a model system and solution NMR spectroscopy. In the absence of Mg²⁺, helices linked by bulges with n ≥ 3 residues adopt predominantly unstacked conformations (stacked population <15%), whereas one-bulge and two-bulge motifs adopt predominantly stacked conformations (stacked population >74%). In the presence of 3 mM Mg²⁺, the helices predominantly coaxially stack (stacked population >84%), regardless of bulge length, and the midpoint for the Mg²⁺-dependent stacking transition is within threefold regardless of bulge length. In the absence of Mg²⁺, the difference between free energy of interhelical coaxial stacking across the bulge variants is estimated to be ∼2.9 kcal/mol, based on an NMR chemical shift mapping with stacking being more energetically disfavored for the longer bulges. This difference decreases to ∼0.4 kcal/mol in the presence of Mg²⁺ NMR RDCs and resonance intensity data show increased dynamics in the stacked state with increasing bulge length in the presence of Mg²⁺ We propose that Mg²⁺ helps to neutralize the growing electrostatic repulsion in the stacked state with increasing bulge length thereby increasing the number of coaxial conformations that are sampled. Energetically compensated interhelical stacking dynamics may help to maximize the conformational adaptability of RNA and allow a wide range of conformations to be optimally stabilized by proteins and ligands.