Impact of RNA interference on gene networks

Application of RNAi technology: a novel approach to navigate abiotic stresses

BACKGROUND

Due to the rising population globally, and the demand for food, it is critical to significantly increase crop production by 2050. However, climate change estimates show that droughts and heatwaves will become more prevalent in many parts of the world, posing a severe danger to food output.

METHODS

Selective breeding based on genetic diversity is falling short of meeting the expanding need for food and feed. However, the advent of modern plant genetic engineering, genome editing, and synthetic biology provides precise techniques for producing crops capable of sustaining yield under stress situations.

RESULTS

As a result, crop varieties with built-in genetic tolerance to environmental challenges are desperately needed. In the recent years, small RNA (sRNA) data has progressed to become one of the most effective approaches for the improvement of crops. So many sRNAs (18-30nt) have been found with the use of hi-tech bioinformatics and sequencing techniques which are involved in the regulation of sequence specific gene noncoding RNAs (short ncRNAs) i.e., microRNA (miRNA) and small interfering RNA (siRNA). Such research outcomes may advance our understanding of the genetic basis of adaptability of plants to various environmental challenges and the genetic variation of plant's tolerance to a number of abiotic stresses.

CONCLUSION

The review article highlights current trends and advances in sRNAs' critical role in responses of plants to drought, heat, cold, and salinity, and also the potential technology that identifies the abiotic stress-regulated sRNAs, and techniques for analyzing and validating the target genes.

Kinetic Modeling to Accelerate the Development of Nucleic Acid Formulations

A critical hurdle in the clinical translation of nucleic acid drugs is the inefficiency in testing formulations for therapeutic potential. Specifically, the ability to quantitatively predict gene expression is lacking when transitioning between cell culture and animal studies. We address this challenge by developing a mathematical framework that can reliably predict short-interfering RNA (siRNA)-mediated gene silencing with as few as one experimental data point as an input, evaluate the efficacies of existing formulations in an expeditious manner, and ultimately guide the design of nanocarriers with optimized performances. The model herein consisted of only essential rate-limiting steps and parameters with easily characterizable values of the RNA interference process, enabling the easy identification of which parameters play dominant roles in determining the potencies of siRNA formulations. Predictions from our framework were in close agreement with in vitro and in vivo experimental results across a retrospective analysis using multiple published data sets. Notably, our findings suggested that siRNA dilution was the primary determinant of gene-silencing kinetics. Our framework shed light on the fact that this dilution rate is governed by different parameters, i.e., cell dilution (in vitro) versus clearance from target tissue (in vivo), highlighting a key reason why in vitro experiments do not always predict in vivo outcomes. Moreover, although our current effort focuses on siRNA, we anticipate that the framework can be modified and applied to other nucleic acids, such as mRNA, that rely on similar biological processes.

Uncovering the Roles of MicroRNAs in Major Depressive Disorder: From Candidate Diagnostic Biomarkers to Treatment Response Indicators

Major depressive disorder (MDD) is a recurrent debilitating illness that represents a major health burden due to its increasing worldwide prevalence, unclear pathological mechanism, nonresponsive treatment, and lack of reliable and specific diagnostic biomarkers. Recently, microRNA species (miRs) have gained particular interest because they have the ability to post-transcriptionally regulate gene expression by modulating mRNA stability and translation in a cohesive fashion. By regulating entire genetic circuitries, miRs have been shown to have dysregulated expression levels in blood samples from MDD patients, when compared to healthy subjects. In addition, antidepressant treatment (AD) also appears to alter the expression pattern of several miRs. Therefore, we critically and systematically reviewed herein the studies assessing the potential biomarker role of several candidate miRs for MDD, as well as treatment response monitoring indicators, in order to enrich the current knowledge and facilitate possible diagnostic biomarker development for MDD, which could aid in reducing both patients' burden and open novel avenues toward a better understanding of MDD neurobiology.

RNA therapeutics in ophthalmology - translation to clinical trials

The use of RNA interference technology has proven to inhibit the expression of many target genes involved in the underlying pathogenesis of several diseases affecting various systems. First established in in vitro and later in animal studies, small interfering RNA (siRNA) and antisense oligonucleotide (ASO) therapeutics are now entering clinical trials with the potential of clinical translation to patients. Gene-silencing therapies have demonstrated promising responses in ocular disorders, predominantly due to the structure of the eye being a closed and compartmentalised organ. However, although the efficacy of such treatments has been observed in both preclinical studies and clinical trials, there are issues pertaining to the use of these drugs which require more extensive research with regards to the delivery and stability of siRNAs and ASOs. This would improve their use for long-term treatment regimens and alleviate the difficulties experienced by patients with ocular diseases. This review provides a detailed insight into the recent developments and clinical trials that have been conducted for several gene-silencing therapies, including ISTH0036, SYL040012, SYL1001, PF-04523655, Sirna-027, QR-110, QR-1123, QR-421a and IONIS-FB-L_RX in glaucoma, dry eye disease, age-related macular degeneration, diabetic macular oedema and various inherited retinal diseases. Our aim is to explore the potential of these drugs whilst evaluating their associated advantages and disadvantages, and to discuss the future translation of RNA therapeutics in ophthalmology.

miR-138 Increases Depressive-Like Behaviors by Targeting SIRT1 in Hippocampus

BACKGROUND

Major depressive disorder (MDD) is a serious and common mood disorder with unknown etiology. Emerging evidence has demonstrated the critical roles of SIRT1 and microRNAs (miRNAs) in the progression of MDD. However, the underlying molecular mechanisms remain to be fully understood.

METHODS

In the present study, the expression level of miR-138 and SIRT1 were analyzed by RT-PCR or Western blotting in a chronic unpredictable mild stress (CUMS) model. The depressive-like behaviors were analyzed by forced swimming test (FST) and sucrose preference test (SPT) in mice injected with miR-138 and SIRT1 overexpression lentivirus. The luciferase reporter assay was used to assess the direct regulation of miR-138 on SIRT1 expression.

RESULTS

The upregulation of miR-138 was found in the hippocampus of the CUMS mice and correlated with decreased SIRT1 expression. C57BL/6J mice treated with SIRT1- and miR-138-expressing (miR-138) lentivirus showed increased depressive-like behaviors. In contrast, SIRT1 or si-miR-138 lentivirus treated C57BL/6J mice showed decreased depressive-like behaviors. Moreover, the Sirt1/PGC-1α/FNDC5/BDNF pathway was downregulated following miR-138 overexpression and increased upon miR-138 knockdown in hippocampus in CUMS mice and cultured primary neuronal cells. Mechanistically, luciferase reporter assay demonstrated that SIRT1 gene was a downstream transcriptional target of miR-138.

CONCLUSION

Our data demonstrated the regulation role of miR-138 on SIRT1 gene expression, miR-138 increased depressive-like behaviors by regulating SIRT1 expression in hippocampus.

Single-cell kinetics of siRNA-mediated mRNA degradation

RNA interference (RNAi) enables the therapeutic use of small interfering RNAs (siRNAs) to silence disease-related genes. The efficiency of silencing is commonly assessed by measuring expression levels of the target protein at a given time point post-transfection. Here, we determine the siRNA-induced fold change in mRNA degradation kinetics from single-cell fluorescence time-courses obtained using live-cell imaging on single-cell arrays (LISCA). After simultaneous transfection of mRNAs encoding eGFP (target) and CayRFP (reference), the eGFP expression is silenced by siRNA. The single-cell time-courses are fitted using a mathematical model of gene expression. Analysis yields best estimates of related kinetic rate constants, including mRNA degradation constants. We determine the siRNA-induced changes in kinetic rates and their correlations between target and reference protein expression. Assessment of mRNA degradation constants using single-cell time-lapse imaging is fast (<30 h) and returns an accurate, time-independent measure of siRNA-induced silencing, thus allowing the exact evaluation of siRNA therapeutics.

Dual-controlled optogenetic system for the rapid down-regulation of protein levels in mammalian cells

Optogenetic switches are emerging molecular tools for studying cellular processes as they offer higher spatiotemporal and quantitative precision than classical, chemical-based switches. Light-controllable gene expression systems designed to upregulate protein expression levels meanwhile show performances superior to their chemical-based counterparts. However, systems to reduce protein levels with similar efficiency are lagging behind. Here, we present a novel two-component, blue light-responsive optogenetic OFF switch ('Blue-OFF'), which enables a rapid and quantitative down-regulation of a protein upon illumination. Blue-OFF combines the first light responsive repressor KRAB-EL222 with the protein degradation module B-LID (blue light-inducible degradation domain) to simultaneously control gene expression and protein stability with a single wavelength. Blue-OFF thus outperforms current optogenetic systems for controlling protein levels. The system is described by a mathematical model which aids in the choice of experimental conditions such as light intensity and illumination regime to obtain the desired outcome. This approach represents an advancement of dual-controlled optogenetic systems in which multiple photosensory modules operate synergistically. As exemplified here for the control of apoptosis in mammalian cell culture, the approach opens up novel perspectives in fundamental research and applications such as tissue engineering.

Engineering approaches in siRNA delivery

siRNAs are very potent drug molecules, able to silence genes involved in pathologies development. siRNAs have virtually an unlimited therapeutic potential, particularly for the treatment of inflammatory diseases. However, their use in clinical practice is limited because of their unfavorable properties to interact and not to degrade in physiological environments. In particular they are large macromolecules, negatively charged, which undergo rapid degradation by plasmatic enzymes, are subject to fast renal clearance/hepatic sequestration, and can hardly cross cellular membranes. These aspects seriously impair siRNAs as therapeutics. As in all the other fields of science, siRNAs management can be advantaged by physical-mathematical descriptions (modeling) in order to clarify the involved phenomena from the preparative step of dosage systems to the description of drug-body interactions, which allows improving the design of delivery systems/processes/therapies. This review analyzes a few mathematical modeling approaches currently adopted to describe the siRNAs delivery, the main procedures in siRNAs vectors' production processes and siRNAs vectors' release from hydrogels, and the modeling of pharmacokinetics of siRNAs vectors. Furthermore, the use of physical models to study the siRNAs vectors' fate in blood stream and in the tissues is presented. The general view depicts a framework maybe not yet usable in therapeutics, but with promising possibilities for forthcoming applications.

Circulating Plasma Micro RNAs in Patients with Major Depressive Disorder Treated with Antidepressants: A Pilot Study

OBJECTIVE

Significant progress was made in the understanding etiopathogenic factors related to MDD, including through research on the role of micro RNAs (miRs). We investigated plasma miRs as potential markers for MDD in patients treated with antidepressants.

METHODS

At the initiation and at the end of twelve weeks of treatment, blood samples were collected and a structured diagnostic interview and a standardized depression rating scale for the presence and severity of major depression were done. The average decrease in HAMD score was 76.89%. Plasma miR expression profiling was performed by real time PCR. The lists of up-regulated (cut-off=2) and down-regulated miRs were imported into the miRWalk2.0 algorithm and used for target predictions. KEGG database pathways analysis was used to retrieve the pathways significantly targeted by at least two of the miRs.

RESULTS

Of the 222 miRs detected in plasma samples of MDD patients, 40 were differentially expressed after treatment. Twenty-three miRs were significantly overexpressed with fold changes between 1.85 and 25.42, and 17 miRs were significantly downregulated with fold changes from 0.28 to 0.68. Pathway analysis revealed a list of 29 pathways for up-regulated miRs, and 20 pathways for down-regulated miRs. Six dysregulated miRs are common to all the top five pathways (Wnt signaling, Cancer, Endocytosis, Axon guidance, MAPK signaling): miR-146a-5p, miR-146b-5p, miR-221-3p, miR-24-3p, miR-26a-5p.

CONCLUSION

Overall, our miRWalk analysis of changes in plasma microRNAs after treatment of patients with major depression might open a new avenue for the understanding of Escitalopram mode of action and for its side effects.

Chronic corticosterone-mediated dysregulation of microRNA network in prefrontal cortex of rats: relevance to depression pathophysiology

Stress plays a major role in inducing depression, which may arise from interplay between complex cascades of molecular and cellular events that influence gene expression leading to altered connectivity and neural plasticity. In recent years, microRNAs (miRNAs) have carved their own niche owing to their innate ability to induce disease phenotype by regulating expression of a large number of genes in a cohesive and coordinated manner. In this study, we examined whether miRNAs and associated gene networks have a role in chronic corticosterone (CORT; 50 mg  kg(-1) × 21 days)-mediated depression in rats. Rats given chronic CORT showed key behavioral features that resembled depression phenotype. Expression analysis revealed differential regulation of 26 miRNAs (19 upregulated, 7 downregulated) in prefrontal cortex of CORT-treated rats. Interaction between altered miRNAs and target genes showed dense interconnected molecular network, in which multiple genes were predicated to be targeted by the same miRNA. A majority of altered miRNAs showed binding sites for glucocorticoid receptor element, suggesting that there may be a common regulatory mechanism of miRNA regulation by CORT. Functional clustering of predicated target genes yielded disorders such as developmental, inflammatory and psychological that could be relevant to depression. Prediction analysis of the two most prominently affected miRNAs miR-124 and miR-218 resulted into target genes that have been shown to be associated with depression and stress-related disorders. Altogether, our study suggests miRNA-mediated novel mechanism by which chronic CORT may be involved in depression pathophysiology.

Emerging role of microRNAs in major depressive disorder: diagnosis and therapeutic implications

Major depressive disorder (MDD) is a major public health concern. Despite tremendous advances, the pathogenic mechanisms associated with MDD are still unclear. Moreover, a significant number of MDD subjects do not respond to the currently available medication. MicroRNAs (miRNAs) are a class of small noncoding RNAs that control gene expression by modulating translation, messenger RNA (mRNA) degradation, or stability of mRNA targets. The role of miRNAs in disease pathophysiology is emerging rapidly. Recent studies demonstrating the involvement of miRNAs in several aspects of neural plasticity, neurogenesis, and stress response, and more direct studies in human postmortem brain provide strong evidence that miRNAs can not only play a critical role in MDD pathogenesis, but can also open up new avenues for the development of therapeutic targets. Circulating miRNAs are now being considered as possible biomarkers in disease pathogenesis and in monitoring therapeutic responses because of the presence and/or release of miRNAs in blood cells as well as in other peripheral tissues. In this review, these aspects are discussed in a comprehensive and critical manner.

Stable inhibition of mmu-miR-466h-5p improves apoptosis resistance and protein production in CHO cells

MiRNAs have been shown to be involved in regulation of multiple cellular processes including apoptosis. Since a single miRNA can affect the expression of several genes, the utilization of miRNAs for apoptosis engineering in mammalian cells can be more efficient than the conventional approach of manipulating a single gene. Mmu-miR-466h-5p was previously shown to have a pro-apoptotic role in CHO cells by reducing the expression of several anti-apoptotic genes and its transient inhibition delayed both the activation of Caspase-3/7 and the loss of cell viability. The present study evaluates the effect of stable inhibition of mmu-miR-466h-5p in CHO cells on their ability to resist apoptosis onset and their production properties. The expression of mmu-miR-466h-5p in the engineered anti-miR-466h CHO cell line was significantly lower than in the negative control and the parental CHO cells. These engineered cells reached higher maximum viable cell density and extended viability compared with negative control and parental CHO cells in batch cell cultures which resulted in the 53.8% and 41.6% increase of integral viable cells. The extended viability of anti-miR-466h CHO cells was the result of delayed Caspase-3/7 activation by more than 35h, and the increased levels of its anti-apoptotic gene targets (smo, stat5a, dad1, birc6, and bcl2l2) to between 2.1- and 12.5-fold compared with the negative control CHO in apoptotic conditions. The expression of secreted alkaline phosphatase (SEAP) increased 43% and the cell-specific productivity increased 11% in the stable pools of anti-miR-466h CHO compared with the stable pools of negative control CHO cells. The above results demonstrate the potential of this novel approach to create more productive cell lines through stable manipulation of specific miRNA expression.

A kinetic model for RNA-interference of focal adhesions

BACKGROUND

Focal adhesions are integrin-based cell-matrix contacts that transduce and integrate mechanical and biochemical cues from the environment. They develop from smaller and more numerous focal complexes under the influence of mechanical force and are key elements for many physiological and disease-related processes, including wound healing and metastasis. More than 150 different proteins localize to focal adhesions and have been systematically classified in the adhesome project (http://www.adhesome.org). First RNAi-screens have been performed for focal adhesions and the effect of knockdown of many of these components on the number, size, shape and location of focal adhesions has been reported.

RESULTS

We have developed a kinetic model for RNA interference of focal adhesions which represents some of its main elements: a spatially layered structure, signaling through the small GTPases Rac and Rho, and maturation from focal complexes to focal adhesions under force. The response to force is described by two complementary scenarios corresponding to slip and catch bond behavior, respectively. Using estimated and literature values for the model parameters, three time scales of the dynamics of RNAi-influenced focal adhesions are identified: a sub-minute time scale for the assembly of focal complexes, a sub-hour time scale for the maturation to focal adhesions, and a time scale of days that controls the siRNA-mediated knockdown. Our model shows bistability between states dominated by focal complexes and focal adhesions, respectively. Catch bonding strongly extends the range of stability of the state dominated by focal adhesions. A sensitivity analysis predicts that knockdown of focal adhesion components is more efficient for focal adhesions with slip bonds or if the system is in a state dominated by focal complexes. Knockdown of Rho leads to an increase of focal complexes.

CONCLUSIONS

The suggested model provides a kinetic description of the effect of RNA-interference of focal adhesions. Its predictions are in good agreement with known experimental results and can now guide the design of RNAi-experiments. In the future, it can be extended to include more components of the adhesome. It also could be extended by spatial aspects, for example by the differential activation of the Rac- and Rho-pathways in different parts of the cell.

A synthetic post-transcriptional controller to explore the modular design of gene circuits

The assembly from modular parts is an efficient approach for creating new devices in Synthetic Biology. In the "bottom-up" designing strategy, modular parts are characterized in advance, and then mathematical modeling is used to predict the outcome of the final device. A prerequisite for bottom-up design is that the biological parts behave in a modular way when assembled together. We designed a new synthetic device for post-transcriptional regulation of gene expression and tested if the outcome of the device could be described from the features of its components. Modular parts showed unpredictable behavior when assembled in different complex circuits. This prevented a modular description of the device that was possible only under specific conditions. Our findings shed doubts into the feasibility of a pure bottom-up approach in synthetic biology, highlighting the urgency for new strategies for the rational design of synthetic devices.

Modeling RNA interference in mammalian cells

Background

RNA interference (RNAi) is a regulatory cellular process that controls post-transcriptional gene silencing. During RNAi double-stranded RNA (dsRNA) induces sequence-specific degradation of homologous mRNA via the generation of smaller dsRNA oligomers of length between 21-23nt (siRNAs). siRNAs are then loaded onto the RNA-Induced Silencing multiprotein Complex (RISC), which uses the siRNA antisense strand to specifically recognize mRNA species which exhibit a complementary sequence. Once the siRNA loaded-RISC binds the target mRNA, the mRNA is cleaved and degraded, and the siRNA loaded-RISC can degrade additional mRNA molecules. Despite the widespread use of siRNAs for gene silencing, and the importance of dosage for its efficiency and to avoid off target effects, none of the numerous mathematical models proposed in literature was validated to quantitatively capture the effects of RNAi on the target mRNA degradation for different concentrations of siRNAs. Here, we address this pressing open problem performing in vitro experiments of RNAi in mammalian cells and testing and comparing different mathematical models fitting experimental data to in-silico generated data. We performed in vitro experiments in human and hamster cell lines constitutively expressing respectively EGFP protein or tTA protein, measuring both mRNA levels, by quantitative Real-Time PCR, and protein levels, by FACS analysis, for a large range of concentrations of siRNA oligomers.

Results

We tested and validated four different mathematical models of RNA interference by quantitatively fitting models' parameters to best capture the in vitro experimental data. We show that a simple Hill kinetic model is the most efficient way to model RNA interference. Our experimental and modeling findings clearly show that the RNAi-mediated degradation of mRNA is subject to saturation effects.

Conclusions

Our model has a simple mathematical form, amenable to analytical investigations and a small set of parameters with an intuitive physical meaning, that makes it a unique and reliable mathematical tool. The findings here presented will be a useful instrument for better understanding RNAi biology and as modelling tool in Systems and Synthetic Biology.

An engineered mammalian band-pass network

Gene expression circuitries, which enable cells to detect precise levels within a morphogen concentration gradient, have a pivotal impact on biological processes such as embryonic pattern formation, paracrine and autocrine signalling, and cellular migration. We present the rational synthesis of a synthetic genetic circuit exhibiting band-pass detection characteristics. The components, involving multiply linked mammalian trans-activator and -repressor control systems, were selected and fine-tuned to enable the detection of ‘low-threshold’ morphogen (tetracycline) concentrations, in which target gene expression was triggered, and a ‘high-threshold’ concentration, in which expression was muted. In silico predictions and supporting experimental findings indicated that the key criterion for functional band-pass detection was the matching of componentry that enabled sufficient separation of the low and high threshold points. Using the circuitry together with a fluorescence-encoded target gene, mammalian cells were genetically engineered to be capable of forming a band-like pattern of differentiation in response to a tetracycline chemical gradient. Synthetic gene networks designed to emulate naturally occurring gene behaviours provide not only insight into biological processes, but may also foster progress in future tissue engineering, gene therapy and biosensing applications.

Avoiding transcription factor competition at promoter level increases the chances of obtaining oscillation

Background

The ultimate goal of synthetic biology is the conception and construction of genetic circuits that are reliable with respect to their designed function (e.g. oscillators, switches). This task remains still to be attained due to the inherent synergy of the biological building blocks and to an insufficient feedback between experiments and mathematical models. Nevertheless, the progress in these directions has been substantial.

Results

It has been emphasized in the literature that the architecture of a genetic oscillator must include positive (activating) and negative (inhibiting) genetic interactions in order to yield robust oscillations. Our results point out that the oscillatory capacity is not only affected by the interaction polarity but by how it is implemented at promoter level. For a chosen oscillator architecture, we show by means of numerical simulations that the existence or lack of competition between activator and inhibitor at promoter level affects the probability of producing oscillations and also leaves characteristic fingerprints on the associated period/amplitude features.

Conclusions

In comparison with non-competitive binding at promoters, competition drastically reduces the region of the parameters space characterized by oscillatory solutions. Moreover, while competition leads to pulse-like oscillations with long-tail distribution in period and amplitude for various parameters or noisy conditions, the non-competitive scenario shows a characteristic frequency and confined amplitude values. Our study also situates the competition mechanism in the context of existing genetic oscillators, with emphasis on the Atkinson oscillator.

Toward a system-level understanding of microRNA pathway via mathematical modeling

The microRNA (miRNA) pathway plays multiple roles in regulating mechanisms controlling both physiological and pathological processes such as the cell proliferation and cancers. But little is known about the dynamic properties, key rate-limiting steps as well as the stochastic noise in this pathway. Presently, a system-theoretic approach was presented to analyze and quantitative modeling of a generic miRNA pathway, which can be implemented deterministically and stochastically. Our results show that the inferred dynamic properties obtained from the mathematical models of the miRNA pathway are well consistent with previous experimental observations. By sensitivity analysis, the key steps in this pathway were found to be the miRNA gene transcription, RISC decay and mRNA formation. In addition, the results of quantified noise strength along the pathway demonstrate that the pathway can reduce the ingress noise and reveal the noise robustness property. Our findings also present testable hypothesis for experimental biologists to further investigate miRNA's increasing functional roles in regulating various cellular processes.

Synthetic gene networks: the next wave in biotechnology?

Engineering novel, reusable gene networks to provide greater control over cellular processes is one of the goals of the emerging discipline of synthetic biology. This article reviews the landmark literature pertaining to the development of synthetic gene networks, the engineering framework used to design and characterize them and the technological developments on the horizon that could potentially advance the field in new directions. As gene network engineering enters its second decade, an attempt is also made to outline the challenges in advancing this nascent field, especially with regard to the practical limitations of component reusability and reliability and the opportunities that present themselves in the development of novel gene expression controllers and single-cell biosensors.

Model-guided design of ligand-regulated RNAi for programmable control of gene expression

Progress in constructing biological networks will rely on the development of more advanced components that can be predictably modified to yield optimal system performance. We have engineered an RNA-based platform, which we call an shRNA switch, that provides for integrated ligand control of RNA interference (RNAi) by modular coupling of an aptamer, competing strand, and small hairpin (sh)RNA stem into a single component that links ligand concentration and target gene expression levels. A combined experimental and mathematical modelling approach identified multiple tuning strategies and moves towards a predictable framework for the forward design of shRNA switches. The utility of our platform is highlighted by the demonstration of fine-tuning, multi-input control, and model-guided design of shRNA switches with an optimized dynamic range. Thus, shRNA switches can serve as an advanced component for the construction of complex biological systems and offer a controlled means of activating RNAi in disease therapeutics.

Computational modeling of post-transcriptional gene regulation by microRNAs

MicroRNAs (miRNAs) have recently emerged as a new complex layer of gene regulation. MiRNAs act post-transcriptionally, influencing the stability, compartmentalization, and translation of their target mRNAs. Computational efforts to understand the post-transcriptional gene regulation by miRNAs have been focused on the target prediction tools, while quantitative kinetic models of gene regulation by miRNAs have so far largely been overlooked. We here develop a kinetic model of post-transcriptional gene regulation by miRNAs, focusing on the miRNAs' effect on increasing the target mRNAs degradation rates. The model is fitted to a temporal microarray dataset where human mRNAs are measured upon transfection with a specific miRNA (miRNA124a). The proposed model exhibits good fit with many target mRNA profiles, indicating that such type of models can be used for studying post-transcriptional gene regulation by miRNA. In particular, the proposed kinetic model can be used for quantifying the miRNA-mediated effects on its targets in the miRNA mis-expression experiments. The model makes an experimentally verifiable prediction of the miRNA124a decay rate, quantifies the miRNA-mediated effect on the target mRNAs degradation, and yields a good correspondence between the inferred and experimentally measured decay rates of human target mRNAs.

Intronically encoded siRNAs improve dynamic range of mammalian gene regulation systems and toggle switch

Applications of conditional gene expression, whether for therapeutic or basic research purposes, are increasingly requiring mammalian gene control systems that exhibit far tighter control properties. While numerous approaches have been used to improve the widely used Tet-regulatory system, many applications, particularly with respect to the engineering of synthetic gene networks, will require a broader range of tightly performing gene control systems. Here, a generically applicable approach is described that utilizes intronically encoded siRNA on the relevant transregulator construct, and siRNA sequence-specific tags on the reporter construct, to minimize basal gene activity in the off-state of a range of common gene control systems. To demonstrate tight control of residual expression the approach was successfully used to conditionally express the toxic proteins RipDD and Linamarase. The intronic siRNA concept was also extended to create a new generation of compact, single-vector, autoinducible siRNA vectors. Finally, using improved regulation systems a mammalian epigenetic toggle switch was engineered that exhibited superior in vitro and in vivo induction characteristics in mice compared to the equivalent non-intronic system.

Mammalian synthetic biology: Engineering of sophisticated gene networks

With the recent development of a wide range of inducible mammalian transgene control systems it has now become possible to create functional synthetic gene networks by linking and connecting systems into various configurations. The past 5 years has thus seen the design and construction of the first synthetic mammalian gene regulatory networks. These networks have built upon pioneering advances in prokaryotic synthetic networks and possess an impressive range of functionalities that will some day enable the engineering of sophisticated inter- and intra-cellular functions to become a reality. At a relatively simple level, the modular linking of transcriptional components has enabled the creation of genetic networks that are strongly analogous to the architectural design and functionality of electronic circuits. Thus, by combining components in different serial or parallel configurations it is possible to produce networks that follow strict logic in integrating multiple independent signals (logic gates and transcriptional cascades) or which temporally modify input signals (time-delay circuits). Progressing in terms of sophistication, synthetic transcriptional networks have also been constructed which emulate naturally occurring genetic properties, such as bistability or dynamic instability. Toggle switches which possess "memory" so as to remember transient administered inputs, hysteric switches which are resistant to stochastic fluctuations in inputs, and oscillatory networks which produce regularly timed expression outputs, are all examples of networks that have been constructed using such properties. Initial steps have also been made in designing the above networks to respond not only to exogenous signals, but also endogenous signals that may be associated with aberrant cellular function or physiology thereby providing a means for tightly controlled gene therapy applications. Moving beyond pure transcriptional control, synthetic networks have also been created which utilize phenomena, such as post-transcriptional silencing, translational control, or inter-cellular signaling to produce novel network-based control both within and between cells. It is envisaged in the not-too-distant future that these networks will provide the basis for highly sophisticated genetic manipulations in biopharmaceutical manufacturing, gene therapy and tissue engineering applications.

Multi-gene engineering: Simultaneous expression and knockdown of six genes off a single platform

Increases in our understanding of gene function have greatly expanded the repertoire of possible genetic interventions at our disposal with the consequence that many genetic engineering applications require multiple manipulations in which target genes can be both overexpressed and silenced in a simple and co-ordinated manner. Using synthetic introns as a source of encoding short-interfering RNA (siRNA), we demonstrate that it is possible to simultaneously express both a transgene and siRNA from a single polymerase (Pol) II promoter. By encoding siRNA as an intron between two protein domains requiring successful splicing for functionality, it was possible to demonstrate that splicing was occurring, that the coding genes (exonic transgenes) resulted in functional protein, and that the spliced siRNA-containing lariat was capable of modulating expression of a separate target gene. We subsequently extended this concept to develop pTRIDENT-based multi-cistronic vectors that were capable of co-ordinated expression of up to three siRNAs and three transgenes off a single genetic platform. Such multi-gene engineering technology, enabling concomitant transgene overexpression and target gene knockdown, should be useful for therapeutic, biopharmaceutical production, and basic research applications.