Repression Strength Research Articles

Design and Characterization of a Transcriptional Repression Toolkit for Plants.

Regulation of gene expression is essential for all life. Tools to manipulate the gene expression level have therefore proven to be very valuable in efforts to engineer biological systems. However, there are few well-characterized genetic parts that reduce gene expression in plants, commonly known as transcriptional repressors. We characterized the repression activity of a library consisting of repression motifs from approximately 25% of the members of the largest known family of repressors. Combining sequence information with our trans-regulatory function data, we next generated a library of synthetic transcriptional repression motifs with function predicted in advance. After characterizing our synthetic library, we demonstrated not only that many of our synthetic constructs were functional as repressors but also that our advance predictions of repression strength were better than random guesses. Finally, we assessed the functionality of known transcriptional repression motifs from a wide range of eukaryotes. Our study represents the largest plant repressor motif library experimentally characterized to date, providing unique opportunities for tuning transcription in plants.

Graded-CRISPRi, a Tool for Tuning the Strengths of CRISPRi-Mediated Knockdowns in Vibrio natriegens Using gRNA Libraries.

In recent years, the fast-growing bacterium Vibrio natriegens has gained increasing attention as it has the potential to become a next-generation chassis for synthetic biology. A wide range of genetic parts and genome engineering methods have already been developed. However, there is still a need for a well-characterized tool to effectively and gradually reduce the expression levels of native genes. To bridge this gap, we created graded-CRISPRi, a system utilizing gRNA variants that lead to varying levels of repression strength. By incorporating multiple gRNA sequences into our design, we successfully extended this concept to simultaneously repress four distinct reporter genes. Furthermore, we demonstrated the capability of using graded-CRISPRi to target native genes, thereby examining the effect of various knockdown levels on growth.

Characterizing microRNA-mediated modulation of gene expression noise and its effect on synthetic gene circuits.

MicroRNAs (miRNAs) have been shown to modulate gene expression noise, but less is known about how miRNAs with different properties may regulate noise differently. Here, we investigate the role of competing RNAs and the composition of miRNA response elements (MREs) in modulating noise. We find that weak competing RNAs could introduce lower noise than strong competing RNAs. In comparison with a single MRE, both repetitive and composite MREs can reduce the noise at low expression, but repetitive MREs can elevate the noise remarkably at high expression. We further observed the behavior of a synthetic cell-type classifier with miRNAs as inputs and find that miRNAs and MREs that could introduce higher noise tend to enhance cell state transition. These results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and the utilization of miRNAs to modulate the behavior of synthetic gene circuits.

Nonequilibrium model of short-range repression in gene transcription regulation.

Transcription factors are proteins that regulate gene activity by activating or repressing gene transcription. A special class of transcriptional repressors operates via a short-range mechanism, making local DNA regions inaccessible to binding by activators, and thus providing an indirect repressive action on the target gene. This mechanism is commonly modeled assuming that repressors interact with DNA under thermodynamic equilibrium and neglecting some configurations of the gene regulatory region. We elaborate on a more general nonequilibrium model of short-range repression using the graph formalism for transitions between gene states, and we apply analytical calculations to compare it with the equilibrium model in terms of the repression strength and expression noise. In contrast to the equilibrium approach, the new model allows us to separate two basic mechanisms of short-range repression. The first mechanism is associated with the recruiting of factors that mediate chromatin condensation, and the second one concerns the blocking of factors that mediate chromatin loosening. The nonequilibrium model demonstrates better performance on previously published gene expression data obtained for transcription factors controlling Drosophila development, and furthermore it predicts that the first repression mechanism is the most favorable in this system. The presented approach can be scaled to larger gene networks and can be used to infer specific modes and parameters of transcriptional regulation from gene expression data.

Repression by the Arabidopsis TOPLESS corepressor requires association with the core mediator complex.

The plant corepressor TOPLESS (TPL) is recruited to a large number of loci that are selectively induced in response to developmental or environmental cues, yet the mechanisms by which it inhibits expression in the absence of these stimuli are poorly understood. Previously, we had used the N-terminus of Arabidopsis thaliana TPL to enable repression of a synthetic auxin response circuit in Saccharomyces cerevisiae (yeast). Here, we leveraged the yeast system to interrogate the relationship between TPL structure and function, specifically scanning for repression domains. We identified a potent repression domain in Helix 8 located within the CRA domain, which directly interacted with the Mediator middle module subunits Med21 and Med10. Interactions between TPL and Mediator were required to fully repress transcription in both yeast and plants. In contrast, we found that multimer formation, a conserved feature of many corepressors, had minimal influence on the repression strength of TPL.

Developing an endogenous quorum-sensing based CRISPRi circuit for autonomous and tunable dynamic regulation of multiple targets in Streptomyces

Quorum-sensing (QS) mediated dynamic regulation has emerged as an effective strategy for optimizing product titers in microbes. However, these QS-based circuits are often created on heterologous systems and require careful tuning via a tedious testing/optimization process. This hampers their application in industrial microbes. Here, we design a novel QS circuit by directly integrating an endogenous QS system with CRISPRi (named EQCi) in the industrial rapamycin-producing strain Streptomyces rapamycinicus. EQCi combines the advantages of both the QS system and CRISPRi to enable tunable, autonomous, and dynamic regulation of multiple targets simultaneously. Using EQCi, we separately downregulate three key nodes in essential pathways to divert metabolic flux towards rapamycin biosynthesis and significantly increase its titers. Further application of EQCi to simultaneously regulate these three key nodes with fine-tuned repression strength boosts the rapamycin titer by ∼660%, achieving the highest reported titer (1836 ± 191 mg/l). Notably, compared to static engineering strategies, which result in growth arrest and suboptimal rapamycin titers, EQCi-based regulation substantially promotes rapamycin titers without affecting cell growth, indicating that it can achieve a trade-off between essential pathways and product synthesis. Collectively, this study provides a convenient and effective strategy for strain improvement and shows potential for application in other industrial microorganisms.

CRISPRi-dCas12a: A dCas12a-Mediated CRISPR Interference for Repression of Multiple Genes and Metabolic Engineering in Cyanobacteria.

In cyanobacteria, metabolic engineering using synthetic biology tools is limited to build a biosolar cell factory that converts CO2 to value-added chemicals, as repression of essential genes has not been achieved. In this study, we developed a dCas12a-mediated CRISPR interference system (CRISPRi-dCas12a) in cyanobacteria that effectively blocked the transcriptional initiation by means of a CRISPR-RNA (crRNA) and 19-nt direct repeat, resulting in 53-94% gene repression. The repression of multiple genes in a single crRNA array was also successfully achieved without a loss in repression strength. In addition, as a demonstration of the dCas12a-mediated CRISPRi for metabolic engineering, photosynthetic squalene production was improved by repressing the essential genes of either acnB encoding for aconitase or cpcB2 encoding for phycocyanin β-subunit in Synechococcus elongatus PCC 7942. The ability to regulate gene repression will promote the construction of biosolar cell factories to produce value-added chemicals.

DUF3669, a \u201cdomain of unknown function\u201d within ZNF746 and ZNF777, oligomerizes and contributes to transcriptional repression

BackgroundZNF746 and ZNF777 belong to a subset of the large Krüppel-associated box (KRAB) zinc finger (ZNF) transcription factor family. They contain, like four other members in human, an additional conserved domain, the “domain of unknown function 3669” (DUF3669). Previous work on members of this subfamily suggested involvement in transcriptional regulation and aberrant ZNF746 overexpression leads to neuronal cell death in Parkinson’s disease.ResultsHere we demonstrate that N-terminal protein segments of the ZNF746a major isoform and ZNF777 act in concert to exert moderate transcriptional repression activities. Full potency depended on the intact configuration consisting of DUF3669, a variant KRAB domain and adjacent sequences. While DUF3669 contributes an intrinsic weak inhibitory activity, the isolated KRAB-AB domains did not repress. Importantly, DUF3669 provides a novel protein-protein interaction interface and mediates direct physical interaction between the members of the subfamily in oligomers. The ZNF746 protein segment encoded by exons 5 and 6 boosted repressor potency, potentially due to the presence of an acceptor lysine for sumoylation at K189. Repressor activity of the potent canonical ZNF10 KRAB domain was not augmented by heterologous transfer of DUF3669, pointing to the importance of context for DUF3669’s impact on transcription. Neither ZNF746a nor ZNF777 protein segments stably associated with TRIM28 within cells. Isoform ZNF746b that contains, unlike the major isoform, a full-length KRAB-A subdomain, displayed substantially increased repressor potency. This increase is due to canonical mechanisms known for KRAB domains since it did not take place in HAP1 knockout models of TRIM28 and SETDB1. A glycine to glutamic acid replacement that complies with a bona fide conserved “MLE” sequence within KRAB-A led to a further strong gain in repressor potency to levels comparable to those of the canonical ZNF10 KRAB domain. Each gain of repressive activity was accompanied by an enhanced interaction with TRIM28 protein.ConclusionDUF3669 adds a protein-protein interaction surface to a subgroup of KRAB-ZNF proteins within an N-terminal configuration with variant KRAB and adjacent sequences likely regulated by sumoylation. DUF3669 contributes to transcriptional repression strength and its homo- and hetero-oligomerization characteristics probably extended the regulatory repertoire of KRAB-ZNF transcription factors during amniote evolution.

Variable cellular decision-making behavior in a constant synthetic network topology

BackgroundModules of interacting components arranged in specific network topologies have evolved to perform a diverse array of cellular functions. For a network with a constant topological structure, its function within a cell may still be tuned by changing the number of instances of a particular component (e.g., gene copy number) or by modulating the intrinsic biochemical properties of a component (e.g., binding strength or catalytic efficiency). How such perturbations affect cellular response dynamics remains poorly understood. Here, we explored these effects in a common decision-making motif, cross-antagonism with autoregulation, by synthetically constructing this network in yeast.ResultsWe employed the engineering design strategy of reuse to build this topology with a single protein building block, TetR, creating necessary components through TetR mutations and fusion partners. We then studied the impact of several topology-preserving perturbations – strength of cross-antagonism, number of operator sites in a promoter, and gene dosage – on decision-making behavior. We found that reducing TetR repression strength, which hinders cross-antagonism, resulted in a loss of mutually exclusive cell responses. Unexpectedly, increasing the number of operator sites also impeded decision-making exclusivity, which may be a consequence of the averaging effect that arises when multiple transcriptional activators and repressors are accommodated at a given locus. Stochastic simulations of this topology revealed that, even for networks with high TetR repression strength and a low number of operator sites, increasing gene dosage can reduce exclusivity in response dynamics. We further demonstrated this result experimentally by quantifying gene copy numbers in selected yeast clones with differing phenotypic responses.ConclusionsOur study illustrates how parameters that do not change the topological structure of a decision-making network can nonetheless exert significant influence on its response dynamics. These findings should further inform the study of native motifs, including the effects of topology-preserving mutations, and the robust engineering of synthetic networks.

Artificial Repeat-Structured siRNA Precursors as Tunable Regulators for Saccharomyces cerevisiae.

RNA interference (RNAi) is widely used as a research tool for studying biological systems and implementing artificial genetic circuits that function by modulating RNA concentrations. Here we engineered Saccharomyces cerevisiae containing a heterologous Saccharomyces castelli RNAi system as a test-bed for RNAi-based circuits. Unlike prior approaches, we describe a strategy that leverages repeat-structured siRNA precursors with incrementally sized stems formed from 23 bp-repeats to achieve modular RNAi-based gene regulation. These enable repression strength to be tuned in a systematic manner by changing the size of the siRNA precursor hairpin stem, without modifying the number or sequence of target sites in the target RNA. We demonstrate that this hairpin-based regulation is able to target both cytoplasmic and nuclear localized RNAs and is stable over extended growth periods. This platform enables the targeting of cellular RNAs as a tunable regulatory layer for sophisticated gene circuits in Saccharomyces cerevisiae.

Rapid and Scalable Characterization of CRISPR Technologies Using an E. coli Cell-Free Transcription-Translation System

CRISPR-Cas systems offer versatile technologies for genome engineering, yet their implementation has been outpaced by ongoing discoveries of new Cas nucleases and anti-CRISPR proteins. Here, we present the use of E.coli cell-free transcription-translation (TXTL) systems to vastly improve the speed and scalability of CRISPR characterization and validation. TXTL can express active CRISPR machinery from added plasmids and linear DNA, and TXTL can output quantitative dynamics of DNA cleavage and gene repression-all without protein purification or live cells. We used TXTL to measure the dynamics of DNA cleavage and gene repression for single- andmulti-effector CRISPR nucleases, predict gene repression strength in E.coli, determine the specificities of 24 diverse anti-CRISPR proteins, and develop a fast and scalable screen for protospacer-adjacent motifs that was successfully applied to five uncharacterized Cpf1 nucleases. These examples underscore how TXTL can facilitate the characterization and application of CRISPR technologies across their many uses.

Enabling Graded and Large-Scale Multiplex of Desired Genes Using a Dual-Mode dCas9 Activator in Saccharomyces cerevisiae.

Standard approaches for dCas9-based modification of gene expression are limited in the ability to multiplex targets, establish streamlined cassettes, and utilize commonly studied Pol II promoters. In this work, we repurpose the dCas9-VPR activator to act as a dual-mode activator/repressor that can be programmed solely on the basis of target position at gene loci. Furthermore, we implement this approach using a streamlined Pol II-ribozyme system that allows expression of many sgRNAs from a single transcript. By "stepping" dCas9-VPR within the promoter region and ORF we create graded activation and repression (respectively) of target genes, allowing precise control over multiplexed gene modulation. Expression from the Pol II system increased the net amount of sgRNA production in cells by 3.88-fold relative to the Pol III SNR52 promoter, leading to a significant improvement in dCas9-VPR repression strength. Finally, we utilize our Pol II system to create galactose-inducible switching of gene expression states and multiplex constructs capable of modulating up to 4 native genes from a single vector. Our approach represents a significant step toward minimizing DNA required to assemble CRISPR systems in eukaryotes while enhancing the efficacy (greater repression strength), scale (more sgRNAs), and scope (inducibility) of dCas9-mediated gene regulation.

Pseudogenes regulate parental gene expression via ceRNA network.

The concept of competitive endogenous RNA (ceRNA) was first proposed by Salmena and colleagues. Evidence suggests that pseudogene RNAs can act as a ‘sponge’ through competitive binding of common miRNA, releasing or attenuating repression through sequestering miRNAs away from parental mRNA. In theory, ceRNAs refer to all transcripts such as mRNA, tRNA, rRNA, long non‐coding RNA, pseudogene RNA and circular RNA, because all of them may become the targets of miRNA depending on spatiotemporal situation. As binding of miRNA to the target RNA is not 100% complementary, it is possible that one miRNA can bind to multiple target RNAs and vice versa. All RNAs crosstalk through competitively binding to miRNA via miRNA response elements (MREs) contained within the RNA sequences, thus forming a complex regulatory network. The ratio of a subset of miRNAs to the corresponding number of MREs determines repression strength on a given mRNA translation or stability. An increase in pseudogene RNA level can sequester miRNA and release repression on the parental gene, leading to an increase in parental gene expression. A massive number of transcripts constitute a complicated network that regulates each other through this proposed mechanism, though some regulatory significance may be mild or even undetectable. It is possible that the regulation of gene and pseudogene expression occurring in this manor involves all RNAs bearing common MREs. In this review, we will primarily discuss how pseudogene transcripts regulate expression of parental genes via ceRNA network and biological significance of regulation.

Role of miRNAs and alternative mRNA 3′-end cleavage and polyadenylation of their mRNA targets in cardiomyocyte hypertrophy

miRNAs play critical roles in heart disease. In addition to differential miRNA expression, miRNA-mediated control is also affected by variable miRNA processing or alternative 3′-end cleavage and polyadenylation (APA) of their mRNA targets. To what extent these phenomena play a role in the heart remains unclear. We sought to explore miRNA processing and mRNA APA in cardiomyocytes, and whether these change during cardiac hypertrophy. Thoracic aortic constriction (TAC) was performed to induce hypertrophy in C57BL/6J mice. RNA extracted from cardiomyocytes of sham-treated, pre-hypertrophic (2days post-TAC), and hypertrophic (7days post-TAC) mice was subjected to small RNA- and poly(A)-test sequencing (PAT-Seq). Differential expression analysis matched expectations; nevertheless we identified ~400 mRNAs and hundreds of noncoding RNA loci as altered with hypertrophy for the first time. Although multiple processing variants were observed for many miRNAs, there was little change in their relative proportions during hypertrophy. PAT-Seq mapped ~48,000 mRNA 3′-ends, identifying novel 3′ untranslated regions (3′UTRs) for over 7000 genes. Importantly, hypertrophy was associated with marked changes in APA with a net shift from distal to more proximal mRNA 3′-ends, which is predicted to decrease overall miRNA repression strength. We independently validated several examples of 3′UTR proportion change and showed that alternative 3′UTRs associate with differences in mRNA translation. Our work suggests that APA contributes to altered gene expression with the development of cardiomyocyte hypertrophy and provides a rich resource for a systems-level understanding of miRNA-mediated regulation in physiological and pathological states of the heart.

Genetic Toggle Switch in the Absence of Cooperative Binding: Exact Results.

We present an analytical treatment of a genetic switch model consisting of two mutually inhibiting genes operating without cooperative binding of the corresponding transcription factors. Previous studies have numerically shown that these systems can exhibit bimodal dynamics without possessing two stable fixed points at the deterministic level. We analytically show that bimodality is induced by the noise and find the critical repression strength that controls a transition between the bimodal and nonbimodal regimes. We also identify characteristic polynomial scaling laws of the mean switching time between bimodal states. These results, independent of the model under study, reveal essential differences between these systems and systems with cooperative binding, where there is no critical threshold for bimodality and the mean switching time scales exponentially with the system size.

Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia.

Cells are complex machines capable of processing information by means of an entangled network of molecular interactions. A crucial component of these decision-making systems is the presence of memory and this is also a specially relevant target of engineered synthetic systems. A classic example of memory devices is a 1-bit memory element known as the flip-flop. Such system can be in principle designed using a single-cell implementation, but a direct mapping between standard circuit design and a living circuit can be cumbersome. Here we present a novel computational implementation of a 1-bit memory device using a reliable multicellular design able to behave as a set-reset flip-flop that could be implemented in yeast cells. The dynamics of the proposed synthetic circuit is investigated with a mathematical model using biologically-meaningful parameters. The circuit is shown to behave as a flip-flop in a wide range of parameter values. The repression strength for the NOT logics is shown to be crucial to obtain a good flip-flop signal. Our model also shows that the circuit can be externally tuned to achieve different memory states and dynamics, such as persistent and transient memory. We have characterized the parameter domains for robust memory storage and retrieval as well as the corresponding time response dynamics.

Noise propagation in synthetic gene circuits for metabolic control.

Dynamic control of enzyme expression can be an effective strategy to engineer robust metabolic pathways. It allows a synthetic pathway to self-regulate in response to changes in bioreactor conditions or the metabolic state of the host. The implementation of this regulatory strategy requires gene circuits that couple metabolic signals with the genetic machinery, which is known to be noisy and one of the main sources of cell-to-cell variability. One of the unexplored design aspects of these circuits is the propagation of biochemical noise between enzyme expression and pathway activity. In this article, we quantify the impact of a synthetic feedback circuit on the noise in a metabolic product in order to propose design criteria to reduce cell-to-cell variability. We consider a stochastic model of a catalytic reaction under negative feedback from the product to enzyme expression. On the basis of stochastic simulations and analysis, we show that, depending on the repression strength and promoter strength, transcriptional repression of enzyme expression can amplify or attenuate the noise in the number of product molecules. We obtain analytic estimates for the metabolic noise as a function of the model parameters and show that noise amplification/attenuation is a structural property of the model. We derive an analytic condition on the parameters that lead to attenuation of metabolic noise, suggesting that a higher promoter sensitivity enlarges the parameter design space. In the theoretical case of a switch-like promoter, our analysis reveals that the ability of the circuit to attenuate noise is subject to a trade-off between the repression strength and promoter strength.

MiRmap web: comprehensive microRNA target prediction online

MicroRNAs (miRNAs) posttranscriptionally repress the expression of protein-coding genes. Based on the partial complementarity between miRNA and messenger RNA pairs with a mandatory so-called ‘seed’ sequence, many thousands of potential targets can be identified. Our open-source software library, miRmap, ranks these potential targets with a biologically meaningful criterion, the repression strength. MiRmap combines thermodynamic, evolutionary, probabilistic and sequence-based features, which cover features from TargetScan, PITA, PACMIT and miRanda. Our miRmap web application offers a user-friendly and feature-rich resource for browsing precomputed miRNA target predictions for model organisms, as well as for predicting and ranking targets for user-submitted sequences. MiRmap web integrates sorting, filtering and exporting of results from multiple queries, as well as providing programmatic access, and is available at http://mirmap.ezlab.org.

MiRmap: Comprehensive prediction of microRNA target repression strength

MicroRNAs, or miRNAs, post-transcriptionally repress the expression of protein-coding genes. The human genome encodes over 1000 miRNA genes that collectively target the majority of messenger RNAs (mRNAs). Base pairing of the so-called miRNA ‘seed’ region with mRNAs identifies many thousands of putative targets. Evaluating the strength of the resulting mRNA repression remains challenging, but is essential for a biologically informative ranking of potential miRNA targets. To address these challenges, predictors may use thermodynamic, evolutionary, probabilistic or sequence-based features. We developed an open-source software library, miRmap, which for the first time comprehensively covers all four approaches using 11 predictor features, 3 of which are novel. This allowed us to examine feature correlations and to compare their predictive power in an unbiased way using high-throughput experimental data from immunopurification, transcriptomics, proteomics and polysome fractionation experiments. Overall, target site accessibility appears to be the most predictive feature. Our novel feature based on PhyloP, which evaluates the significance of negative selection, is the best performing predictor in the evolutionary category. We combined all the features into an integrated model that almost doubles the predictive power of TargetScan. miRmap is freely available from http://cegg.unige.ch/mirmap.

Exploring the sequence–function relationship in transcriptional regulation by the lac O1 operator

Understanding how binding of a transcription factor to an operator is influenced by the operator sequence is an ongoing quest. It facilitates discovery of alternative binding sites as well as tuning of transcriptional regulation. We investigated the behavior of the Escherichia coli Lac repressor (LacI) protein with a large set of lac O(1) operator variants. The 114 variants examined contained a mean of 2.9 (range 0-4) mutations at positions -4, -2, +2 and +4 in the minimally required 17 bp operator. The relative affinity of LacI for the operators was examined by quantifying expression of a GFP reporter gene and Rosetta structural modeling. The combinations of mutations in the operator sequence created a wide range of regulatory behaviors. We observed variations in the GFP fluorescent signal among the operator variants of more than an order of magnitude under both uninduced and induced conditions. We found that a single nucleotide change may result in changes of up to six- and 12-fold in uninduced and induced GFP signals, respectively. Among the four positions mutated, we found that nucleotide G at position -4 is strongly correlated with strong repression. By Rosetta modeling, we found a significant correlation between the calculated binding energy and the experimentally observed transcriptional repression strength for many operators. However, exceptions were also observed, underscoring the necessity for further improvement in biophysical models of protein-DNA interactions.