The RNA silencing pathway: the bits and pieces that matter

Biochemical and nanotechnological approaches to combat phytoparasitic nematodes

The foundation of most food production systems underpinning global food security is the careful management of soil resources. Embedded in the concept of soil health is the impact of diverse soil-borne pests and pathogens, and phytoparasitic nematodes represent a particular challenge. Root-knot nematodes and cyst nematodes are severe threats to agriculture, accounting for annual yield losses of US$157 billion. The control of soil-borne phytoparasitic nematodes conventionally relies on the use of chemical nematicides, which can have adverse effects on the environment and human health due to their persistence in soil, plants, and water. Nematode-resistant plants offer a promising alternative, but genetic resistance is species-dependent, limited to a few crops, and breeding and deploying resistant cultivars often takes years. Novel approaches for the control of phytoparasitic nematodes are therefore required, those that specifically target these parasites in the ground whilst minimizing the impact on the environment, agricultural ecosystems, and human health. In addition to the development of next-generation, environmentally safer nematicides, promising biochemical strategies include the combination of RNA interference (RNAi) with nanomaterials that ensure the targeted delivery and controlled release of double-stranded RNA. Genome sequencing has identified more than 75 genes in root knot and cyst nematodes that have been targeted with RNAi so far. But despite encouraging results, the delivery of dsRNA to nematodes in the soil remains inefficient. In this review article, we describe the state-of-the-art RNAi approaches targeting phytoparasitic nematodes and consider the potential benefits of nanotechnology to improve dsRNA delivery.

Genetic manipulation of giant viruses and their host, Acanthamoeba castellanii

Giant viruses (GVs) provide an unprecedented source of genetic innovation in the viral world and are thus, besides their importance in basic and environmental virology, in the spotlight for bioengineering advances. Their host, Acanthamoeba castellanii, is an accidental human pathogen that acts as a natural host and environmental reservoir of other human pathogens. Tools for genetic manipulation of viruses and host were lacking. Here, we provide a detailed method for genetic manipulation of A. castellanii and the GVs it plays host to by using CRISPR-Cas9 or homologous recombination. We detail the steps of vector preparation (4 d), transfection of amoeba cells (1 h), infection (1 h), selection (5 d for viruses, 2 weeks for amoebas) and cloning of recombinant viruses (4 d) or amoebas (2 weeks). This procedure takes ~3 weeks or 1 month for the generation of recombinant viruses or amoebas, respectively. This methodology allows the generation of stable gene modifications, which was not possible by using RNA silencing, the only previously available reverse genetic tool. We also include detailed sample-preparation steps for protein localization by immunofluorescence (4 h), western blotting (4 h), quantification of viral particles by optical density (15 min), calculation of viral lethal dose 50 (7 d) and quantification of DNA replication by quantitative PCR (4 h) to allow efficient broad phenotyping of recombinant organisms. This methodology allows the function of thousands of ORFan genes present in GVs, as well as the complex pathogen-host, pathogen-pathogen or pathogen-symbiont interactions in A. castellanii, to be studied in vivo.

Epigenetic inheritance of gene silencing is maintained by a self-tuning mechanism based on resource competition

Biological systems can maintain memories over long timescales, with examples including memories in the brain and immune system. It is unknown how functional properties of memory systems, such as memory persistence, can be established by biological circuits. To address this question, we focus on transgenerational epigenetic inheritance in Caenorhabditis elegans. In response to a trigger, worms silence a target gene for multiple generations, resisting strong dilution due to growth and reproduction. Silencing may also be maintained indefinitely upon selection according to silencing levels. We show that these properties imply the fine-tuning of biochemical rates in which the silencing system is positioned near the transition to bistability. We demonstrate that this behavior is consistent with a generic mechanism based on competition for synthesis resources, which leads to self-organization around a critical state with broad silencing timescales. The theory makes distinct predictions and offers insights into the design principles of long-term memory systems.

Kinetics of HTT lowering in brain of YAC 128 mice following single and repetitive intranasal dosing of siRNA packaged in chitosan-based nanoparticle

This report describes the kinetics of Huntington's Disease (HD) gene (HTT) lowering in brains of YAC 128 mice. Lowering (or "knock-down") of HTT mRNA expression was achieved by intranasal administration of specially designed siRNA loaded into chitosan nanoparticles. Kinetic patterns of HTT lowering observed in different brain regions allowed calculation of cumulative lowering effects that result from multiple consecutive administrations. Mathematical modeling generated dosing schedules for approaching a steady knock-down effect and for prediction of magnitude and duration of HTT lowering. Kinetic modeling of HTT lowering with our algorithm will be useful in determining intranasal dosing schedules to produce chronic, therapeutically significant lowering effect of gene expression.

The ecology of the genome and the dynamics of the biological dark matter

Transposable elements (TEs) are essential components of the eukaryotic genomes. While mostly deleterious, evidence is mounting that TEs provide the host with beneficial adaptations. How 'selfish' or 'parasitic' DNA persists until it helps species evolution is emerging as a major evolutionary puzzle, especially in asexual taxa where the lack of sex strongly impede the spread of TEs. Since occasional but unchecked TE proliferations would ultimately drive host lineages toward extinction, asexual genomes are typically predicted to be free of TEs, which contrasts with their persistence in asexual taxa. We designed innovative 'Eco-genomic' models that account for both host demography and within-host molecular mechanisms of transposition and silencing to analyze their impact on TE dynamics in asexual genome populations. We unraveled that the spread of TEs can be limited to a stable level by density-dependent purifying selection when TE copies are over-dispersed among lineages and the host demographic turn-over is fast. We also showed that TE silencing can protect host populations in two ways; by preventing TEs with weak effects to accumulate or by favoring the elimination of TEs with large effects. Our predictions may explain TE persistence in known asexual taxa that typically show fast demography and where TE copy number variation between lineages is expected. Such TE persistence in asexual taxa potentially has important implications for their evolvability and the preservation of sexual reproduction.

Physiologically based pharmacokinetic (PBPK) modeling of RNAi therapeutics: Opportunities and challenges

Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool with many demonstrated applications in various phases of drug development and regulatory review. RNA interference (RNAi)-based therapeutics are a class of drugs that have unique pharmacokinetic properties and mechanisms of action. With an increasing number of RNAi therapeutics in the pipeline and reaching the market, there is a considerable amount of active research in this area requiring a multidisciplinary approach. The application of PBPK models for RNAi therapeutics is in its infancy and its utility to facilitate the development of this new class of drugs is yet to be fully evaluated. From this perspective, we briefly discuss some of the current computational modeling approaches used in support of efficient development and approval of RNAi therapeutics. Considerations for PBPK model development are highlighted both in a relative context between small molecules and large molecules such as monoclonal antibodies and as it applies to RNAi therapeutics. In addition, the prospects for drawing upon other recognized avenues of PBPK modeling and some of the foreseeable challenges in PBPK model development for these chemical modalities are briefly discussed. Finally, an exploration of the potential application of PBPK model development for RNAi therapeutics is provided. We hope these preliminary thoughts will help initiate a dialogue between scientists in the relevant sectors to examine the value of PBPK modeling for RNAi therapeutics. Such evaluations could help standardize the practice in the future and support appropriate guidance development for strengthening the RNAi therapeutics development program.

Transcriptomics and solid tumors: The next frontier in precision cancer medicine

Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology.

Characterization of small RNA populations in non-transgenic and aflatoxin-reducing-transformed peanut

Aflatoxin contamination is a major constraint in food production worldwide. In peanut (Arachis hypogaea L.), these toxic and carcinogenic aflatoxins are mainly produced by Aspergillus flavus Link and A. parasiticus Speare. The use of RNA interference (RNAi) is a promising method to reduce or prevent the accumulation of aflatoxin in peanut seed. In this study, we performed high-throughput sequencing of small RNA populations in a control line and in two transformed peanut lines that expressed an inverted repeat targeting five genes involved in the aflatoxin-biosynthesis pathway and that showed up to 100% less aflatoxin B₁ than the controls. The objective was to determine the putative involvement of the small RNA populations in aflatoxin reduction. In total, 41 known microRNA (miRNA) families and many novel miRNAs were identified. Among those, 89 known and 10 novel miRNAs were differentially expressed in the transformed lines. We furthermore found two small interfering RNAs derived from the inverted repeat, and 39 sRNAs that mapped without mismatches to the genome of A. flavus and were present only in the transformed lines. This information will increase our understanding of the effectiveness of RNAi and enable the possible improvement of the RNAi technology for the control of aflatoxins.

Efficient tuning of siRNA dose response by combining mixed polymer nanocarriers with simple kinetic modeling

Two of the most prominent challenges that limit the clinical success of siRNA therapies are a lack of control over cargo release from the delivery vehicle and an incomplete understanding of the link between gene silencing dynamics and siRNA dosing. Herein, we address these challenges through the formulation of siRNA polyplexes containing light-responsive polymer mixtures, whose varied compositions and triggered release behavior provide enhanced gene silencing and controlled dose responses that can be predicted by simple kinetic models. Through the straightforward mixing of two block copolymers, the level of gene knockdown was easily optimized to achieve the maximum level of GAPDH protein silencing in NIH/3T3 cells (~70%) using a single siRNA dose. The kinetic model was used to describe the dynamic changes in mRNA and protein concentrations in response to siRNA treatment. These predictions enabled the application of a second dose of siRNA to maximally suppress gene expression over multiple days, leading to a further 50% reduction in protein levels relative to those measured following a single dose. Furthermore, polyplexes remained dormant in cells until exposed to the photo-stimulus, demonstrating the complete control over siRNA activity as well as the stability of the nanocarriers. Thus, this work demonstrates that pairing advances in biomaterials design with simple kinetic modeling provides new insight into gene silencing dynamics and presents a powerful strategy to control gene expression through siRNA delivery.

STATEMENT OF SIGNIFICANCE

Our manuscript describes two noteworthy impacts: (1) we designed mixed polymer formulations to enhance gene silencing, and (2) we simultaneously developed a simple kinetic model for determining optimal siRNA dose responses to maintain silencing over several days. These advances address critical challenges in siRNA delivery and provide new opportunities in therapeutics development. The structure-function relationships prevalent in these formulations were established to enable tuning and forecasting of nanocarrier efficiency a priori, leading to siRNA dosing regimens able to maximally suppress gene expression. Our advances are significant because the mixed polymer formulations provide a straightforward and scalable approach to tailor siRNA delivery regimens. Moreover, the implementation of accurate dosing frameworks addresses a major knowledge gap that has hindered clinical implementation of siRNA.

RNAi-mediated Control of Aflatoxins in Peanut: Method to Analyze Mycotoxin Production and Transgene Expression in the Peanut/Aspergillus Pathosystem

The Food and Agriculture Organization of the United Nations estimates that 25% of the food crops in the world are contaminated with aflatoxins. That represents 100 million tons of food being destroyed or diverted to non-human consumption each year. Aflatoxins are powerful carcinogens normally accumulated by the fungi Aspergillus flavus and A. parasiticus in cereals, nuts, root crops and other agricultural products. Silencing of five aflatoxin-synthesis genes by RNA interference (RNAi) in peanut plants was used to control aflatoxin accumulation following inoculation with A. flavus. Previously, no method existed to analyze the effectiveness of RNAi in individual peanut transgenic events, as these usually produce few seeds, and traditional methods of large field experiments under aflatoxin-conducive conditions were not an option. In the field, the probability of finding naturally contaminated seeds is often 1/100 to 1/1,000. In addition, aflatoxin contamination is not uniformly distributed. Our method uses few seeds per transgenic event, with small pieces processed for real-time PCR (RT-PCR) or small RNA sequencing, and for analysis of aflatoxin accumulation by ultra-performance liquid chromatography (UPLC). RNAi-expressing peanut lines 288-72 and 288-74, showed up to 100% reduction (p ≤ 0.01) in aflatoxin B1 and B2 compared to the control that accumulated up to 14,000 ng · g(-1) of aflatoxin B1 when inoculated with aflatoxigenic A. flavus. As reference, the maximum total of aflatoxins allowable for human consumption in the United States is 20 ng · g(-1). This protocol describes the application of RNAi-mediated control of aflatoxins in transgenic peanut seeds and methods for its evaluation. We believe that its application in breeding of peanut and other crops will bring rapid advancement in this important area of science, medicine and human nutrition, and will significantly contribute to the international effort to control aflatoxins, and potentially other mycotoxins in major food crops.

RNAi revised--target mRNA-dependent enhancement of gene silencing

The discovery of RNA interference (RNAi) gave rise to the development of new nucleic acid-based technologies as powerful investigational tools and potential therapeutics. Mechanistic key details of RNAi in humans need to be deciphered yet, before such approaches take root in biomedicine and molecular therapy.

We developed and validated an in silico-based model of siRNA-mediated RNAi in human cells in order to link in vitro-derived pre-steady state kinetic data with a quantitative and time-resolved understanding of RNAi on the cellular level. The observation that product release by Argonaute 2 is accelerated in the presence of an excess of target RNA in vitro inspired us to suggest an associative mechanism for the RNA slicer reaction where incoming target mRNAs actively promote dissociation of cleaved mRNA fragments. This novel associative model is compatible with high multiple turnover rates of RNAi-based gene silencing in living cells and accounts for target mRNA concentration-dependent enhancement of the RNAi machinery.

Time-delayed model of immune response in plants

In the studies of plant infections, the plant immune response is known to play an essential role. In this paper we derive and analyse a new mathematical model of plant immune response with particular account for post-transcriptional gene silencing (PTGS). Besides biologically accurate representation of the PTGS dynamics, the model explicitly includes two time delays to represent the maturation time of the growing plant tissue and the non-instantaneous nature of the PTGS. Through analytical and numerical analysis of stability of the steady states of the model we identify parameter regions associated with recovery and resistant phenotypes, as well as possible chronic infections. Dynamics of the system in these regimes is illustrated by numerical simulations of the model.

Dye selection for live cell imaging of intact siRNA

Investigations into the fate of small interfering RNA (siRNA) after transfection may unravel new ways to improve RNA interference (RNAi) efficiency. Because intracellular degradation of RNA may prevent reliable observation of fluorescence-labeled siRNA, new tools for fluorescence microscopy are warranted to cover the considerable duration of the RNAi effect. Here, the characterization and application of new fluorescence resonance energy transfer (FRET) dye pairs for sensing the integrity of duplex siRNA is reported, which allows an assessment of the degradation status of an siRNA cell population by live cell imaging. A panel of high-yield fluorescent dyes has been investigated for their suitability as FRET pairs for the investigation of RNA inside the cell. Nine dyes in 13 FRET pairs were evaluated based on the performance in assays of photostability, cross-excitation, bleed-through, as well as on quantified changes of fluorescence as a consequence of, e.g., RNA strand hybridization and pH variation. The Atto488/Atto590 FRET pair has been applied to live cell imaging, and has revealed first aspects of unusual trafficking of intact siRNA. A time-lapse study showed highly dynamic movement of siRNA in large perinuclear structures. These and the resulting optimized FRET labeled siRNA are expected to have significant impact on future observations of labeled RNAs in living cells.

Multi-scale modeling of tissues using CompuCell3D

The study of how cells interact to produce tissue development, homeostasis, or diseases was, until recently, almost purely experimental. Now, multi-cell computer simulation methods, ranging from relatively simple cellular automata to complex immersed-boundary and finite-element mechanistic models, allow in silico study of multi-cell phenomena at the tissue scale based on biologically observed cell behaviors and interactions such as movement, adhesion, growth, death, mitosis, secretion of chemicals, chemotaxis, etc. This tutorial introduces the lattice-based Glazier-Graner-Hogeweg (GGH) Monte Carlo multi-cell modeling and the open-source GGH-based CompuCell3D simulation environment that allows rapid and intuitive modeling and simulation of cellular and multi-cellular behaviors in the context of tissue formation and subsequent dynamics. We also present a walkthrough of four biological models and their associated simulations that demonstrate the capabilities of the GGH and CompuCell3D.

Modeling antiviral resistance in plants

The goal of this chapter is to describe in simple terms how the use of ordinary differential equation (ODE) modeling, in conjunction with experimentation, can be utilized to improve our understanding of the dynamics of gene silencing and virus resistance in plants.

Transgenerational inheritance of an acquired small RNA-based antiviral response in C. elegans

Induced expression of the Flock House virus in the soma of C. elegans results in the RNAi-dependent production of virus-derived, small-interfering RNAs (viRNAs), which in turn silence the viral genome. We show here that the viRNA-mediated viral silencing effect is transmitted in a non-Mendelian manner to many ensuing generations. We show that the viral silencing agents, viRNAs, are transgenerationally transmitted in a template-independent manner and work in trans to silence viral genomes present in animals that are deficient in producing their own viRNAs. These results provide evidence for the transgenerational inheritance of an acquired trait, induced by the exposure of animals to a specific, biologically relevant physiological challenge. The ability to inherit such extragenic information may provide adaptive benefits to an animal.

Subcellular fate and off-target effects of siRNA, shRNA, and miRNA

RNA interference (RNAi) strategies include double-stranded RNA (dsRNA), small interfering RNA (siRNA), short hairpin RNA (shRNA), and microRNA (miRNA). As this is a highly specific technique, efforts have been made to utilize RNAi towards potential knock down of disease-causing genes in a targeted fashion. RNAi has the potential to selectively inhibit gene expression by degrading or blocking the translation of the target mRNA. However, delivering these RNAs to specific cells presents a significant challenge. Some of these challenges result from the necessity of traversing the circulatory system while avoiding kidney filtration, degradation by endonucleases, aggregation with serum proteins, and uptake by phagocytes. Further, non-specific delivery may result in side-effects, including the activation of immune response. We discuss the challenges in the systemic delivery to target cells, cellular uptake, endosomal release and intracellular transport of RNAi drugs and recent progress in overcoming these barriers. We also discuss approaches that increase the specificity and metabolic stability and reduce the off-target effects of RNAi strategy.

Viral RNAi suppressor reversibly binds siRNA to outcompete Dicer and RISC via multiple turnover

RNA interference is a conserved gene regulatory mechanism employed by most eukaryotes as a key component of their innate immune response to viruses and retrotransposons. During viral infection, the RNase-III-type endonuclease Dicer cleaves viral double-stranded RNA into small interfering RNAs (siRNAs) 21-24 nucleotides in length and helps load them into the RNA-induced silencing complex (RISC) to guide the cleavage of complementary viral RNA. As a countermeasure, many viruses have evolved viral RNA silencing suppressors (RSS) that tightly, and presumably quantitatively, bind siRNAs to thwart RNA-interference-mediated degradation. Viral RSS proteins also act across kingdoms as potential immunosuppressors in gene therapeutic applications. Here we report fluorescence quenching and electrophoretic mobility shift assays that probe siRNA binding by the dimeric RSS p19 from Carnation Italian Ringspot Virus, as well as by human Dicer and RISC assembly complexes. We find that the siRNA:p19 interaction is readily reversible, characterized by rapid binding [(1.69 ± 0.07) × 10(8) M(-)(1) s(-1)] and marked dissociation (k(off)=0.062 ± 0.002 s(-1)). We also observe that p19 efficiently competes with recombinant Dicer and inhibits the formation of RISC-related assembly complexes found in human cell extract. Computational modeling based on these results provides evidence for the transient formation of a ternary complex between siRNA, human Dicer, and p19. An expanded model of RNA silencing indicates that multiple turnover by reversible binding of siRNAs potentiates the efficiency of the suppressor protein. Our predictive model is expected to be applicable to the dosing of p19 as a silencing suppressor in viral gene therapy.

Quantitative analysis of cellular metabolic dissipative, self-organized structures

One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life.

Optimal viral strategies for bypassing RNA silencing

The RNA silencing pathway constitutes a defence mechanism highly conserved in eukaryotes, especially in plants, where the underlying working principle relies on the repressive action triggered by the intracellular presence of double-stranded RNAs. This immune system performs a post-transcriptional suppression of aberrant mRNAs or viral RNAs by small interfering RNAs (siRNAs) that are directed towards their target in a sequence-specific manner. However, viruses have evolved strategies to escape from silencing surveillance while promoting their own replication. Several viruses encode suppressor proteins that interact with different elements of the RNA silencing pathway and block it. The different suppressors are not phylogenetically nor structurally related and also differ in their mechanism of action. Here, we adopt a model-driven forward-engineering approach to understand the evolution of suppressor proteins and, in particular, why viral suppressors preferentially target some components of the silencing pathway. We analysed three strategies characterized by different design principles: replication in the absence of a suppressor, suppressors targeting the first protein component of the pathway and suppressors targeting the siRNAs. Our results shed light on the question of whether a virus must opt for devoting more time into transcription or into translation and on which would be the optimal step of the silencing pathway to be targeted by suppressors. In addition, we discussed the evolutionary implications of such designing principles.

Comparing 2-nt 3' overhangs against blunt-ended siRNAs: a systems biology based study

In this study, we formulate a computational reaction model following a chemical kinetic theory approach to predict the binding rate constant for the siRNA-RISC complex formation reaction. The model allowed us to study the potency difference between 2-nt 3' overhangs against blunt-ended siRNA molecules in an RNA interference (RNAi) system. The rate constant predicted by this model was fed into a stochastic simulation of the RNAi system (using the Gillespie stochastic simulator) to study the overall potency effect. We observed that the stochasticity in the transcription/translation machinery has no observable effects in the RNAi pathway. Sustained gene silencing using siRNAs can be achieved only if there is a way to replenish the dsRNA molecules in the cell. Initial findings show about 1.5 times more blunt-ended molecules will be required to keep the mRNA at the same reduced level compared to the 2-nt overhang siRNAs. However, the mRNA levels jump back to saturation after a longer time when blunt-ended siRNAs are used. We found that the siRNA-RISC complex formation reaction rate was 2 times slower when blunt-ended molecules were used pointing to the fact that the presence of the 2-nt overhangs has a greater effect on the reaction in which the bound RISC complex cleaves the mRNA.

Multicell simulations of development and disease using the CompuCell3D simulation environment

Mathematical modeling and computer simulation have become crucial to biological fields from genomics to ecology. However, multicell, tissue-level simulations of development and disease have lagged behind other areas because they are mathematically more complex and lack easy-to-use software tools that allow building and running in silico experiments without requiring in-depth knowledge of programming. This tutorial introduces Glazier-Graner-Hogeweg (GGH) multicell simulations and CompuCell3D, a simulation framework that allows users to build, test, and run GGH simulations.

RNA silencing can explain chlorotic infection patterns on plant leaves

Background

RNA silencing has been implicated in virus symptom development in plants. One common infection symptom in plants is the formation of chlorotic tissue in leaves. Chlorotic and healthy tissue co-occur on a single leaf and form patterns. It has been shown that virus levels in chlorotic tissue are high, while they are low in healthy tissue. Additionally, the presence of siRNAs is confined to the chlorotic spots and the boundaries between healthy and infected tissue. These results strongly indicate that the interaction between virus growth and RNA silencing plays a role in the formation of infection patterns on leaves. However, how RNA silencing leads to the intricate patterns is not known.

Results

Here we elucidate the mechanisms leading to infection patterns and the conditions which lead to the various patterns observed. We present a modeling approach in which we combine intra- and inter-cellular dynamics of RNA silencing and viral growth. We observe that, due to the spread of viruses and the RNA silencing response, parts of the tissue become infected while other parts remain healthy. As is observed in experiments high virus levels coincide with high levels of siRNAs, and siRNAs are also present in the boundaries between infected and healthy tissue. We study how single- and double-stranded cleavage by Dicer and amplification by RNA-dependent RNA polymerase can affect the patterns formed.

Conclusion

This work shows that RNA silencing and virus growth within a cell, and the local spread of virions and siRNAs between cells can explain the heterogeneous spread of virus in leaf tissue, and therewith the observed infection patterns in plants.

Modeling recursive RNA interference

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments.

Maintaining the silence: reflections on long-term RNAi

Since the demonstration of RNA interference (RNAi) in mammalian cells, considerable research and financial effort has gone towards implementing RNAi as a viable therapeutic platform. RNAi is, without doubt, the most promising strategy for the treatment of human genetic disorders. Because many of the targets proposed for RNAi therapy require chronic treatment, researchers agree that the emphasis must now be placed on the safe and long-term application of RNAi drugs to reap the benefits at last.

The dynamics and efficacy of antiviral RNA silencing: A model study

Background

Mathematical modeling is important to provide insight in the complicated pathway of RNA silencing. RNA silencing is an RNA based mechanism that is widely used by eukaryotes to fight viruses, and to control gene expression.

Results

We here present the first mathematical model that combines viral growth with RNA silencing. The model involves a plus-strand RNA virus that replicates through a double-strand RNA intermediate. The model of the RNA silencing pathway consists of cleavage of viral RNA into siRNA by Dicer, target cleavage of viral RNA via the RISC complex, and a secondary response. We found that, depending on the strength of the silencing response, different viral growth patterns can occur. Silencing can decrease viral growth, cause oscillations, or clear the virus completely. Our model can explain various observed phenomena, even when they seem contradictory at first: the diverse responses to the removal of RNA dependent RNA polymerase; different viral growth curves; and the great diversity in observed siRNA ratios.

Conclusion

The model presented here is an important step in the understanding of the natural functioning of RNA silencing in viral infections.

Impact of RNA interference on gene networks

Small endogenous RNAs such as microRNAs (miRNAs) and small interfering RNAs (siRNAs) have been found to post-transcriptionally control cellular gene networks by targeting complementary mRNAs for translation impairment (miRNA) or destruction (siRNA). We have developed a computational model, coordinated to molecular and biochemical parameters of RNA interference pathways, to provide (semi-) quantitative insight into the molecular events managing siRNA-mediated gene expression silencing in native and synthetic gene networks. Based on mass-conservation principles and kinetic rate laws, we converted biochemical RNA interference pathways into a set of ordinary differential equations that describe the dynamics of siRNA-mediated translation-regulation in mammalian cells. Capitalizing on mechanistic details of synthetic transactivator operation, we wired this model into a transcription control circuitry in which the siRNA and its target mRNA are independently regulated at the transcriptional level. In this context, we studied the impact of siRNA transcription timing on the onset of target gene transcription and production kinetics of target mRNA-encoded proteins. We also simulated the rate of siRNA-induced mRNA depletion and demonstrated that the relative concentrations of interacting siRNAs/mRNAs and the number of siRNA-specific target sites on a transcript modulate (i) the rate of target mRNA disappearance, (ii) the steady-state mRNA levels and (iii) induction dynamics of mRNA-encoded protein production. As our model predictions are consistent with available biochemical parameters, extrapolations may improve our understanding of how complex regulatory gene networks are impacted by small endogenous RNAs.

Insights into the kinetics of siRNA-mediated gene silencing from live-cell and live-animal bioluminescent imaging

Small interfering RNA (siRNA) molecules are potent effectors of post-transcriptional gene silencing. Using noninvasive bioluminescent imaging and a mathematical model of siRNA delivery and function, the effects of target-specific and treatment-specific parameters on siRNA-mediated gene silencing are monitored in cells stably expressing the firefly luciferase protein. In vitro, luciferase protein levels recover to pre-treatment values within <1 week in rapidly dividing cell lines, but take longer than 3 weeks to return to steady-state levels in nondividing fibroblasts. Similar results are observed in vivo, with knockdown lasting ∼10 days in subcutaneous tumors in A/J mice and 3–4 weeks in the nondividing hepatocytes of BALB/c mice. These data indicate that dilution due to cell division, and not intracellular siRNA half-life, governs the duration of gene silencing under these conditions. To demonstrate the practical use of the model in treatment design, model calculations are used to predict the dosing schedule required to maintain persistent silencing of target proteins with different half-lives in rapidly dividing or nondividing cells. The approach of bioluminescent imaging combined with mathematical modeling provides useful insights into siRNA function and may help expedite the translation of siRNA into clinically relevant therapeutics for disease treatment and management.

How do adaptive immune systems control pathogens while avoiding autoimmunity?

Immune systems face a daunting control challenge. On the one hand, they need to minimize damage from pathogens, without wasting energy and resources, but on the other must avoid initiating or perpetuating autoimmune responses. Finally, because pathogens interfere with immune function, immune systems must be robust against sabotage. We describe here how these challenges are met by two immune systems, the intracellular RNA interference system and the vertebrate CD8 T-cell response. We extrapolate from these two systems to propose principles for strategically robust control.