Mapping the operational landscape of microRNAs in synthetic gene circuits

Engineering and standardization of posttranscriptional biocircuitry in Saccharomyces cerevisiae

This short review considers to what extent posttranscriptional steps of gene expression can provide the basis for novel control mechanisms and procedures in synthetic biology and biotechnology. The term biocircuitry is used here to refer to functionally connected components comprising DNA, RNA or proteins. The review begins with an overview of the diversity of devices being developed and then considers the challenges presented by trying to engineer more scaled-up systems. While the engineering of RNA-based and protein-based circuitry poses new challenges, the resulting 'toolsets' of components and novel mechanisms of operation will open up multiple new opportunities for synthetic biology. However, agreed procedures for standardization will need to be placed at the heart of this expanding field if the full potential benefits are to be realized.

Uncoupling gene expression noise along the central dogma using genome engineered human cell lines

Eukaryotic protein synthesis is an inherently stochastic process. This stochasticity stems not only from variations in cell content between cells but also from thermodynamic fluctuations in a single cell. Ultimately, these inherently stochastic processes manifest as noise in gene expression, where even genetically identical cells in the same environment exhibit variation in their protein abundances. In order to elucidate the underlying sources that contribute to gene expression noise, we quantify the contribution of each step within the process of protein synthesis along the central dogma. We uncouple gene expression at the transcriptional, translational, and post-translational level using custom engineered circuits stably integrated in human cells using CRISPR. We provide a generalized framework to approximate intrinsic and extrinsic noise in a population of cells expressing an unbalanced two-reporter system. Our decomposition shows that the majority of intrinsic fluctuations stem from transcription and that coupling the two genes along the central dogma forces the fluctuations to propagate and accumulate along the same path, resulting in increased observed global correlation between the products.

Robust Filtering and Noise Suppression in Intragenic miRNA-Mediated Host Regulation

MicroRNAs (miRNAs) are short non-coding RNA molecules that regulate gene expression post-transcriptionally by binding to target messenger RNAs (mRNAs). Many human miRNAs are intragenic, located within introns of protein-coding sequence (host). Intriguingly, a percentage of intragenic miRNAs downregulate the host transcript forming an incoherent feedforward motif topology. Here, we study intragenic miRNA-mediated host gene regulation using a synthetic gene circuit stably integrated within a safe-harbor locus of human cells. When the intragenic miRNA is directed to inhibit the host transcript, we observe a reduction in reporter expression accompanied by output filtering and noise reduction. Specifically, the system operates as a filter with respect to promoter strength, with the threshold being robust to promoter strength and measurement time. Additionally, the intragenic miRNA regulation reduces expression noise compared to splicing-alone architecture. Our results provide a new insight into miRNA-mediated gene expression, with direct implications to gene therapy and synthetic biology applications.

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Intragenic miRNA-based host regulation was recreated using a synthetic miRNA

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The system was integrated in HEK293 cells via CRISPR-based safe-harbor integration

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The system generates a gene expression threshold robust to host promoter strength

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Host gene output has reduced noise compared to a splicing-alone architecture

Genomic competition for noise reduction shaped evolutionary landscape of mir-4673

The genomic platform that informs evolution of microRNA cascades remains unknown. Here we capitalised on the recent evolutionary trajectory of hominin-specific miRNA-4673, encoded in intron 4 of notch-1, to uncover the identity of one such precursor genomic element and the selective forces acting upon it. The miRNA targets genes that regulate Wnt/β-catenin signalling cascade. Primary sequence of the microRNA and its target region in Wnt modulating genes evolved from homologous signatures mapped to homotypic cis-clusters recognised by TCF3/4 and TFAP2A/B/C families. Integration of homologous TFAP2A/B/C cis-clusters (short range inhibitor of β-catenin) into the transcriptional landscape of Wnt cascade genes can reduce noise in gene expression. Probabilistic adoption of miRNA secondary structure by one such cis-signature in notch-1 reflected selection for superhelical curvature symmetry of precursor DNA to localise a nucleosome that overlapped the latter cis-cluster. By replicating the cis-cluster signature, non-random interactions of the miRNA with key Wnt modulator genes expanded the transcriptional noise buffering capacity via a coherent feed-forward loop mechanism. In consequence, an autonomous transcriptional noise dampener (the cis-cluster/nucleosome) evolved into a post-transcriptional one (the miRNA). The findings suggest a latent potential for remodelling of transcriptional landscape by miRNAs that capitalise on non-random distribution of genomic cis-signatures.

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.

Engineering grass biomass for sustainable and enhanced bioethanol production

Bioethanol from lignocellulosic biomass is a promising step for the future energy requirements. Grass is a potential lignocellulosic biomass which can be utilised for biorefinery-based bioethanol production. Grass biomass is a suitable feedstock for bioethanol production due to its all the year around production, requirement of less fertile land and noninterference with food system. However, the processes involved, i.e. pretreatment, enzymatic hydrolysis and fermentation for bioethanol production from grass biomass, are both time consuming and costly. Developing the grass biomass in planta for enhanced bioethanol production is a promising step for maximum utilisation of this valuable feedstock and, thus, is the focus of the present review. Modern breeding techniques and transgenic processes are attractive methods which can be utilised for development of the feedstock. However, the outcomes are not always predictable and the time period required for obtaining a robust variety is generation dependent. Sophisticated genome editing technologies such as synthetic genetic circuits (SGC) or clustered regularly interspaced short palindromic repeats (CRISPR) systems are advantageous for induction of desired traits/heritable mutations in a foreseeable genome location in the 1st mutant generation. Although, its application in grass biomass for bioethanol is limited, these sophisticated techniques are anticipated to exhibit more flexibility in engineering the expression pattern for qualitative and qualitative traits. Nevertheless, the fundamentals rendered by the genetics of the transgenic crops will remain the basis of such developments for obtaining biorefinery-based bioethanol concepts from grass biomass. Grasses which are abundant and widespread in nature epitomise attractive lignocellulosic feedstocks for bioethanol production. The complexity offered by the grass cell wall in terms of lignin recalcitrance and its binding to polysaccharides forms a barricade for its commercialization as a biofuel feedstock. Inspired by the possibilities for rewiring the genetic makeup of grass biomass for reduced lignin and lignin-polysaccharide linkages along with increase in carbohydrates, innovative approaches for in planta modifications are forging ahead. In this review, we highlight the progress made in the field of transgenic grasses for bioethanol production and focus our understanding on improvements of simple breeding techniques and post-harvest techniques for development in shortening of lignin-carbohydrate and carbohydrate-carbohydrate linkages. Further, we discuss about the designer lignins which are aimed for qualitable lignins and also emphasise on remodelling of polysaccharides and mixed-linkage glucans for enhancing carbohydrate content and in planta saccharification efficiency. As a final point, we discuss the role of synthetic genetic circuits and CRISPR systems in targeted improvement of cell wall components without compromising the plant growth and health. It is anticipated that this review can provide a rational approach towards a better understanding of application of in planta genetic engineering aspects for designing synthetic genetic circuits which can promote grass feedstocks for biorefinery-based bioethanol concepts.

Role of network-mediated stochasticity in mammalian drug resistance

A major challenge in biology is that genetically identical cells in the same environment can display gene expression stochasticity (noise), which contributes to bet-hedging, drug tolerance, and cell-fate switching. The magnitude and timescales of stochastic fluctuations can depend on the gene regulatory network. Currently, it is unclear how gene expression noise of specific networks impacts the evolution of drug resistance in mammalian cells. Answering this question requires adjusting network noise independently from mean expression. Here, we develop positive and negative feedback-based synthetic gene circuits to decouple noise from the mean for Puromycin resistance gene expression in Chinese Hamster Ovary cells. In low Puromycin concentrations, the high-noise, positive-feedback network delays long-term adaptation, whereas it facilitates adaptation under high Puromycin concentration. Accordingly, the low-noise, negative-feedback circuit can maintain resistance by acquiring mutations while the positive-feedback circuit remains mutation-free and regains drug sensitivity. These findings may have profound implications for chemotherapeutic inefficiency and cancer relapse.

The role of gene expression noise in the evolution of drug resistance in mammalian cells is unclear. Here, by uncoupling noise from mean expression of a drug resistance gene in CHO cells the authors show that noisy expression aids adaptation to high drug levels, but delays it at low drug levels.

Multifunctional miR-155 Pathway in Avian Oncogenic Virus-Induced Neoplastic Diseases

MicroRNAs (miRNAs) are small noncoding RNAs that fine-tune the responses of the cell by modulating the cell transcriptome and gene expression. MicroRNA 155 (miR-155) is a conserved multifunctional miRNA involved in multiple roles including the modulation of the immune responses. When deregulated, miR-155 can also contribute to cancer as has been demonstrated in several human malignancies such as diffuse large B cell lymphoma, chronic lymphocytic leukemia, as well as in Epstein⁻Barr virus (EBV)-induced B cell transformation. Avian oncogenic viruses such as Marek's disease virus (MDV), avian leukosis virus (ALV), and reticuloendotheliosis virus (REV) that account for more than 90% of cancers in avian species, also make use of the miR-155 pathway during oncogenesis. While oncogenic retroviruses, such as ALV, activate miR-155 by insertional activation, acutely transforming retroviruses use transduced oncogenes such as v-rel to upregulate miR-155 expression. MDV on the other hand, encodes a functional miR-155 ortholog mdv1-miR-M4, similar to the miR-155 ortholog kshv-miR-K11 present in Kaposi's sarcoma-associated herpesvirus (KSHV). We have shown that mdv1-miR-M4 is critical for the induction of MDV-induced lymphomas further demonstrating the oncogenic potential of miR-155 pathway in cancers irrespective of the diverse etiology. In this review, we discuss on our current understanding of miR-155 function in virus-induced lymphomas focusing primarily on avian oncogenic viruses.

Synthetic Mutualism and the Intervention Dilemma

Ecosystems are complex networks of interacting individuals co-evolving with their environment. As such, changes to an interaction can influence the whole ecosystem. However, to predict the outcome of these changes, considerable understanding of processes driving the system is required. Synthetic biology provides powerful tools to aid this understanding, but these developments also allow us to change specific interactions. Of particular interest is the ecological importance of mutualism, a subset of cooperative interactions. Mutualism occurs when individuals of different species provide a reciprocal fitness benefit. We review available experimental techniques of synthetic biology focused on engineered synthetic mutualistic systems. Components of these systems have defined interactions that can be altered to model naturally occurring relationships. Integrations between experimental systems and theoretical models, each informing the use or development of the other, allow predictions to be made about the nature of complex relationships. The predictions range from stability of microbial communities in extreme environments to the collapse of ecosystems due to dangerous levels of human intervention. With such caveats, we evaluate the promise of synthetic biology from the perspective of ethics and laws regarding biological alterations, whether on Earth or beyond. Just because we are able to change something, should we?

Synthetic RNA-based logic computation in mammalian cells

Synthetic biological circuits are designed to regulate gene expressions to control cell function. To date, these circuits often use DNA-delivery methods, which may lead to random genomic integration. To lower this risk, an all RNA system, in which the circuit and delivery method are constituted of RNA components, is preferred. However, the construction of complexed circuits using RNA-delivered devices in living cells has remained a challenge. Here we show synthetic mRNA-delivered circuits with RNA-binding proteins for logic computation in mammalian cells. We create a set of logic circuits (AND, OR, NAND, NOR, and XOR gates) using microRNA (miRNA)- and protein-responsive mRNAs as decision-making controllers that are used to express transgenes in response to intracellular inputs. Importantly, we demonstrate that an apoptosis-regulatory AND gate that senses two miRNAs can selectively eliminate target cells. Thus, our synthetic RNA circuits with logic operation could provide a powerful tool for future therapeutic applications.