Double-stemmed and split structural variants of fluorescent RNA Mango aptamers.

Aptamers with fluorogenic ligands are emerging as useful tools to quantify and track RNA molecules. The RNA Mango family of aptamers have a useful combination of tight ligand binding, bright fluorescence, and small size. However, the simple structure of these aptamers, with a single base-paired stem capped by a G-quadruplex, can limit the sequence and structural modifications needed for many use-inspired designs. Here we report new structural variants of RNA Mango that have two base-paired stems attached to the quadruplex. Fluorescence saturation analysis of one of the double-stemmed constructs showed a maximum fluorescence that is ∼75% brighter than the original single-stemmed Mango I. A small number of mutations to nucleotides in the tetraloop-like linker of the second stem were subsequently analyzed. The effect of these mutations on the affinity and fluorescence suggested that the nucleobases of the second linker do not directly interact with the fluorogenic ligand (TO1-biotin), but may instead induce higher fluorescence by indirectly altering the ligand properties in the bound state. The effects of the mutations in this second tetraloop-like linker indicate the potential of this second stem for rational design and reselection experiments. Additionally, we demonstrated that a bimolecular mango designed by splitting the double-stemmed Mango can function when two RNA molecules are cotranscribed from different DNA templates in a single in vitro transcription. This bimolecular Mango has potential application in detecting RNA-RNA interactions. Together, these constructs expand the designability of the Mango aptamers to facilitate future applications of RNA imaging.

Dynamic RNA Fitness Landscapes of a Group I Ribozyme during Changes to the Experimental Environment.

Fitness landscapes of protein and RNA molecules can be studied experimentally using high-throughput techniques to measure the functional effects of numerous combinations of mutations. The rugged topography of these molecular fitness landscapes is important for understanding and predicting natural and experimental evolution. Mutational effects are also dependent upon environmental conditions, but the effects of environmental changes on fitness landscapes remains poorly understood. Here, we investigate the changes to the fitness landscape of a catalytic RNA molecule while changing a single environmental variable that is critical for RNA structure and function. Using high-throughput sequencing of in vitro selections, we mapped a fitness landscape of the Azoarcus group I ribozyme under eight different concentrations of magnesium ions (1-48 mM MgCl2). The data revealed the magnesium dependence of 16,384 mutational neighbors, and from this, we investigated the magnesium induced changes to the topography of the fitness landscape. The results showed that increasing magnesium concentration improved the relative fitness of sequences at higher mutational distances while also reducing the ruggedness of the mutational trajectories on the landscape. As a result, as magnesium concentration was increased, simulated populations evolved toward higher fitness faster. Curve-fitting of the magnesium dependence of individual ribozymes demonstrated that deep sequencing of in vitro reactions can be used to evaluate the structural stability of thousands of sequences in parallel. Overall, the results highlight how environmental changes that stabilize structures can also alter the ruggedness of fitness landscapes and alter evolutionary processes.

Hidden intermediates in Mango III RNA aptamer folding revealed by pressure perturbation.

Fluorescent RNA aptamers have the potential to enable routine quantitation and localization of RNA molecules and serve as models for understanding biologically active aptamers. In recent years, several fluorescent aptamers have been selected and modified to improve their properties, revealing that small changes to the RNA or the ligands can modify significantly their fluorescent properties. Although structural biology approaches have revealed the bound, ground state of several fluorescent aptamers, characterization of low-abundance, excited states in these systems is crucial to understanding their folding pathways. Here we use pressure as an alternative variable to probe the suboptimal states of the Mango III aptamer with both fluorescence and NMR spectroscopy approaches. At moderate KCl concentrations, increasing pressure disrupted the G-quadruplex structure of the Mango III RNA and led to an intermediate with lower fluorescence. These observations indicate the existence of suboptimal RNA structural states that still bind the TO1-biotin fluorophore and moderately enhance fluorescence. At higher KCl concentration as well, the intermediate fluorescence state was populated at high pressure, but the G-quadruplex remained stable at high pressure, supporting the notion of parallel folding and/or binding pathways. These results demonstrate the usefulness of pressure for characterizing RNA folding intermediates.

Experimental Resurrection of Ancestral Mammalian CPEB3 Ribozymes Reveals Deep Functional Conservation.

Self-cleaving ribozymes are genetic elements found in all domains of life, but their evolution remains poorly understood. A ribozyme located in the second intron of the cytoplasmic polyadenylation binding protein 3 gene (CPEB3) shows high sequence conservation in mammals, but little is known about the functional conservation of self-cleaving ribozyme activity across the mammalian tree of life or during the course of mammalian evolution. Here, we use a phylogenetic approach to design a mutational library and a deep sequencing assay to evaluate the in vitro self-cleavage activity of numerous extant and resurrected CPEB3 ribozymes that span over 100 My of mammalian evolution. We found that the predicted sequence at the divergence of placentals and marsupials is highly active, and this activity has been conserved in most lineages. A reduction in ribozyme activity appears to have occurred multiple different times throughout the mammalian tree of life. The in vitro activity data allow an evaluation of the predicted mutational pathways leading to extant ribozyme as well as the mutational landscape surrounding these ribozymes. The results demonstrate that in addition to sequence conservation, the self-cleavage activity of the CPEB3 ribozyme has persisted over millions of years of mammalian evolution.

Phased nucleotide inserts for sequencing low-diversity RNA samples from in vitro selection experiments.

In vitro selection combined with high-throughput sequencing is a powerful experimental approach with broad application in the engineering and characterization of RNA molecules. Diverse pools of starting sequences used for selection are often flanked by fixed sequences used as primer binding sites. These low diversity regions often lead to data loss from complications with Illumina image processing algorithms. A common method to alleviate this problem is the addition of fragmented bacteriophage PhiX genome, which improves sequence quality but sacrifices a portion of usable sequencing reads. An alternative approach is to insert nucleotides of variable length and composition ("phased inserts") at the beginning of each molecule when adding sequencing adaptors. This approach preserves read depth but reduces the length of each read. Here, we test the ability of phased inserts to replace PhiX in a low-diversity sample generated for a high-throughput sequencing based ribozyme activity screen. We designed a pool of 4096 RNA sequence variants of the self-cleaving twister ribozyme from Oryza sativa For each unique sequence, we determined the fraction of ribozyme cleaved during in vitro transcription via deep sequencing on an Illumina MiSeq. We found that libraries with the phased inserts produced high-quality sequence data without the addition of PhiX. We found good agreement between previously published data on twister ribozyme variants and our data produced with phased inserts even when PhiX was omitted. We conclude that phased inserts can be implemented following in vitro selection experiments to reduce or eliminate the use of PhiX and maximize read depth.

Genotype network intersections promote evolutionary innovation.

Evolutionary innovations are qualitatively novel traits that emerge through evolution and increase biodiversity. The genetic mechanisms of innovation remain poorly understood. A systems view of innovation requires the analysis of genotype networks-the vast networks of genetic variants that produce the same phenotype. Innovations can occur at the intersection of two different genotype networks. However, the experimental characterization of genotype networks has been hindered by the vast number of genetic variants that need to be functionally analyzed. Here, we use high-throughput sequencing to study the fitness landscape at the intersection of the genotype networks of two catalytic RNA molecules (ribozymes). We determined the ability of numerous neighboring RNA sequences to catalyze two different chemical reactions, and we use these data as a proxy for a genotype to fitness map where two functions come in close proximity. We find extensive functional overlap, and numerous genotypes can catalyze both functions. We demonstrate through evolutionary simulations that these numerous points of intersection facilitate the discovery of a new function. However, the rate of adaptation of the new function depends upon the local ruggedness around the starting location in the genotype network. As a consequence, one direction of adaptation is more rapid than the other. We find that periods of neutral evolution increase rates of adaptation to the new function by allowing populations to spread out in their genotype network. Our study reveals the properties of a fitness landscape where genotype networks intersect and the consequences for evolutionary innovations. Our results suggest that historic innovations in natural systems may have been facilitated by overlapping genotype networks.

Ribonucleoprotein purification and characterization using RNA Mango.

The characterization of RNA-protein complexes (RNPs) is a difficult but increasingly important problem in modern biology. By combining the compact RNA Mango aptamer with a fluorogenic thiazole orange desthiobiotin (TO1-Dtb or TO3-Dtb) ligand, we have created an RNA tagging system that simplifies the purification and subsequent characterization of endogenous RNPs. Mango-tagged RNP complexes can be immobilized on a streptavidin solid support and recovered in their native state by the addition of free biotin. Furthermore, Mango-based RNP purification can be adapted to different scales of RNP isolation ranging from pull-down assays to the isolation of large amounts of biochemically defined cellular RNPs. We have incorporated the Mango aptamer into the S. cerevisiae U1 small nuclear RNA (snRNA), shown that the Mango-snRNA is functional in cells, and used the aptamer to pull down a U1 snRNA-associated protein. To demonstrate large-scale isolation of RNPs, we purified and characterized bacterial RNA polymerase holoenzyme (HE) in complex with a Mango-containing 6S RNA. We were able to use the combination of a red-shifted TO3-Dtb ligand and eGFP-tagged HE to follow the binding and release of the 6S RNA by two-color native gel analysis as well as by single-molecule fluorescence cross-correlation spectroscopy. Together these experiments demonstrate how the Mango aptamer in conjunction with simple derivatives of its flurophore ligands enables the purification and characterization of endogenous cellular RNPs in vitro.

Spontaneous network formation among cooperative RNA replicators.

The origins of life on Earth required the establishment of self-replicating chemical systems capable of maintaining and evolving biological information. In an RNA world, single self-replicating RNAs would have faced the extreme challenge of possessing a mutation rate low enough both to sustain their own information and to compete successfully against molecular parasites with limited evolvability. Thus theoretical analyses suggest that networks of interacting molecules were more likely to develop and sustain life-like behaviour. Here we show that mixtures of RNA fragments that self-assemble into self-replicating ribozymes spontaneously form cooperative catalytic cycles and networks. We find that a specific three-membered network has highly cooperative growth dynamics. When such cooperative networks are competed directly against selfish autocatalytic cycles, the former grow faster, indicating an intrinsic ability of RNA populations to evolve greater complexity through cooperation. We can observe the evolvability of networks through in vitro selection. Our experiments highlight the advantages of cooperative behaviour even at the molecular stages of nascent life.

Intramolecular phenotypic capacitance in a modular RNA molecule.

Phenotypic capacitance refers to the ability of a genome to accumulate mutations that are conditionally hidden and only reveal phenotype-altering effects after certain environmental or genetic changes. Capacitance has important implications for the evolution of novel forms and functions, but experimentally studied mechanisms behind capacitance are mostly limited to complex, multicomponent systems often involving several interacting protein molecules. Here we demonstrate phenotypic capacitance within a much simpler system, an individual RNA molecule with catalytic activity (ribozyme). This naturally occurring RNA molecule has a modular structure, where a scaffold module acts as an intramolecular chaperone that facilitates folding of a second catalytic module. Previous studies have shown that the scaffold module is not absolutely required for activity, but dramatically decreases the concentration of magnesium ions required for the formation of an active site. Here, we use an experimental perturbation of magnesium ion concentration that disrupts the folding of certain genetic variants of this ribozyme and use in vitro selection followed by deep sequencing to identify genotypes with altered phenotypes (catalytic activity). We identify multiple conditional mutations that alter the wild-type ribozyme phenotype under a stressful environmental condition of low magnesium ion concentration, but preserve the phenotype under more relaxed conditions. This conditional buffering is confined to the scaffold module, but controls the catalytic phenotype, demonstrating how modularity can enable phenotypic capacitance within a single macromolecule. RNA's ancient role in life suggests that phenotypic capacitance may have influenced evolution since life's origins.

Negative Epistasis in Experimental RNA Fitness Landscapes.

Mutations and their effects on fitness are a fundamental component of evolution. The effects of some mutations change in the presence of other mutations, and this is referred to as epistasis. Epistasis can occur between mutations in different genes or within the same gene. A systematic study of epistasis requires the analysis of numerous mutations and their combinations, which has recently become feasible with advancements in DNA synthesis and sequencing. Here we review the mutational effects and epistatic interactions within RNA molecules revealed by several recent high-throughput mutational studies involving two ribozymes studied in vitro, as well as a tRNA and a snoRNA studied in yeast. The data allow an analysis of the distribution of fitness effects of individual mutations as well as combinations of two or more mutations. Two different approaches to measuring epistasis in the data both reveal a predominance of negative epistasis, such that higher combinations of two or more mutations are typically lower in fitness than expected from the effect of each individual mutation. These data are in contrast to past studies of epistasis that used computationally predicted secondary structures of RNA that revealed a predominance of positive epistasis. The RNA data reviewed here are more similar to that found from mutational experiments on individual protein enzymes, suggesting that a common thermodynamic framework may explain negative epistasis between mutations within macromolecules.

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis.

Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme.

Cryptic variation is caused by the robustness of phenotypes to mutations. Cryptic variation has no effect on phenotypes in a given genetic or environmental background, but it can have effects after mutations or environmental change. Because evolutionary adaptation by natural selection requires phenotypic variation, phenotypically revealed cryptic genetic variation may facilitate evolutionary adaptation. This is possible if the cryptic variation happens to be pre-adapted, or "exapted", to a new environment, and is thus advantageous once revealed. However, this facilitating role for cryptic variation has not been proven, partly because most pertinent work focuses on complex phenotypes of whole organisms whose genetic basis is incompletely understood. Here we show that populations of RNA enzymes with accumulated cryptic variation adapt more rapidly to a new substrate than a population without cryptic variation. A detailed analysis of our evolving RNA populations in genotype space shows that cryptic variation allows a population to explore new genotypes that become adaptive only in a new environment. Our observations show that cryptic variation contains new genotypes pre-adapted to a changed environment. Our results highlight the positive role that robustness and epistasis can have in adaptive evolution.

The effects of stabilizing and directional selection on phenotypic and genotypic variation in a population of RNA enzymes.

The distribution of variation in a quantitative trait and its underlying distribution of genotypic diversity can both be shaped by stabilizing and directional selection. Understanding either distribution is important, because it determines a population's response to natural selection. Unfortunately, existing theory makes conflicting predictions about how selection shapes these distributions, and very little pertinent experimental evidence exists. Here we study a simple genetic system, an evolving RNA enzyme (ribozyme) in which a combination of high throughput genotyping and measurement of a biochemical phenotype allow us to address this question. We show that directional selection, compared to stabilizing selection, increases the genotypic diversity of an evolving ribozyme population. In contrast, it leaves the variance in the phenotypic trait unchanged.

RNA sequence to structure analysis from comprehensive pairwise mutagenesis of multiple self-cleaving ribozymes.

Self-cleaving ribozymes are RNA molecules that catalyze the cleavage of their own phosphodiester backbones. These ribozymes are found in all domains of life and are also a tool for biotechnical and synthetic biology applications. Self-cleaving ribozymes are also an important model of sequence-to-function relationships for RNA because their small size simplifies synthesis of genetic variants and self-cleaving activity is an accessible readout of the functional consequence of the mutation. Here, we used a high-throughput experimental approach to determine the relative activity for every possible single and double mutant of five self-cleaving ribozymes. From this data, we comprehensively identified non-additive effects between pairs of mutations (epistasis) for all five ribozymes. We analyzed how changes in activity and trends in epistasis map to the ribozyme structures. The variety of structures studied provided opportunities to observe several examples of common structural elements, and the data was collected under identical experimental conditions to enable direct comparison. Heatmap-based visualization of the data revealed patterns indicating structural features of the ribozymes including paired regions, unpaired loops, non-canonical structures, and tertiary structural contacts. The data also revealed signatures of functionally critical nucleotides involved in catalysis. The results demonstrate that the data sets provide structural information similar to chemical or enzymatic probing experiments, but with additional quantitative functional information. The large-scale data sets can be used for models predicting structure and function and for efforts to engineer self-cleaving ribozymes.

Environmental change exposes beneficial epistatic interactions in a catalytic RNA.

Natural selection drives populations of individuals towards local peaks in a fitness landscape. These peaks are created by the interactions between individual mutations. Fitness landscapes may change as an environment changes. In a previous contribution, we discovered a variant of the Azoarcus group I ribozyme that represents a local peak in the RNA fitness landscape. The genotype at this peak is distinguished from the wild-type by four point mutations. We here report ribozyme fitness data derived from constructing all possible combinations of these point mutations. We find that these mutations interact epistatically. Importantly, we show that these epistatic interactions change qualitatively in the three different environments that we studied. We find examples where the relative fitness of a ribozyme can change from neutral or negative in one environment, to positive in another. We also show that the fitness effect of a specific GC-AU base pair switch is dependent on both the environment and the genetic context. Moreover, the mutations that we study improve activity at the cost of decreased structural stability. Environmental change is ubiquitous in nature. Our results suggest that such change can facilitate adaptive evolution by exposing new peaks of a fitness landscape. They highlight a prominent role for genotype-environment interactions in doing so.

Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data.

Ribozymes are RNA molecules that catalyze biochemical reactions. Self-cleaving ribozymes are a common naturally occurring class of ribozymes that catalyze site-specific cleavage of their own phosphodiester backbone. In addition to their natural functions, self-cleaving ribozymes have been used to engineer control of gene expression because they can be designed to alter RNA processing and stability. However, the rational design of ribozyme activity remains challenging, and many ribozyme-based systems are engineered or improved by random mutagenesis and selection (in vitro evolution). Improving a ribozyme-based system often requires several mutations to achieve the desired function, but extensive pairwise and higher-order epistasis prevent a simple prediction of the effect of multiple mutations that is needed for rational design. Recently, high-throughput sequencing-based approaches have produced data sets on the effects of numerous mutations in different ribozymes (RNA fitness landscapes). Here we used such high-throughput experimental data from variants of the CPEB3 self-cleaving ribozyme to train a predictive model through machine learning approaches. We trained models using either a random forest or long short-term memory (LSTM) recurrent neural network approach. We found that models trained on a comprehensive set of pairwise mutant data could predict active sequences at higher mutational distances, but the correlation between predicted and experimentally observed self-cleavage activity decreased with increasing mutational distance. Adding sequences with increasingly higher numbers of mutations to the training data improved the correlation at increasing mutational distances. Systematically reducing the size of the training data set suggests that a wide distribution of ribozyme activity may be the key to accurate predictions. Because the model predictions are based only on sequence and activity data, the results demonstrate that this machine learning approach allows readily obtainable experimental data to be used for RNA design efforts even for RNA molecules with unknown structures. The accurate prediction of RNA functions will enable a more comprehensive understanding of RNA fitness landscapes for studying evolution and for guiding RNA-based engineering efforts.

Template-directed RNA polymerization: the taming of the milieu.

No-bias binding: The abiotic template-directed synthesis of RNA could have been a key process in the origins of life on Earth. Recreating this process in the laboratory has been challenging, yet a combination of strategies has given rise to a synthesis that is both efficient and unbiased against any of the four nucleotides.

A multiplexed, automated evolution pipeline enables scalable discovery and characterization of biosensors.

Biosensors are key components in engineered biological systems, providing a means of measuring and acting upon the large biochemical space in living cells. However, generating small molecule sensing elements and integrating them into in vivo biosensors have been challenging. Here, using aptamer-coupled ribozyme libraries and a ribozyme regeneration method, de novo rapid in vitro evolution of RNA biosensors (DRIVER) enables multiplexed discovery of biosensors. With DRIVER and high-throughput characterization (CleaveSeq) fully automated on liquid-handling systems, we identify and validate biosensors against six small molecules, including five for which no aptamers were previously found. DRIVER-evolved biosensors are applied directly to regulate gene expression in yeast, displaying activation ratios up to 33-fold. DRIVER biosensors are also applied in detecting metabolite production from a multi-enzyme biosynthetic pathway. This work demonstrates DRIVER as a scalable pipeline for engineering de novo biosensors with wide-ranging applications in biomanufacturing, diagnostics, therapeutics, and synthetic biology.

Haematophagous ectoparasites lower survival of and have detrimental physiological effects on golden eagle nestlings.

Haematophagous ectoparasites can directly affect the health of young animals by depleting blood volume and reducing energetic resources available for growth and development. Less is known about the effects of ectoparasitism on stress physiology (i.e. glucocorticoid hormones) or animal behaviour. Mexican chicken bugs (Haematosiphon inodorus; Hemiptera: Cimicidae) are blood-sucking ectoparasites that live in nesting material or nest substrate and feed on nestling birds. Over the past 50 years, the range of H. inodorus has expanded, suggesting that new hosts or populations may be vulnerable. We studied the physiological and behavioural effects of H. inodorus on golden eagle (Aquila chrysaetos) nestlings in southwestern Idaho. We estimated the level of H. inodorus infestation at each nest and measured nestling mass, haematocrit, corticosterone concentrations, telomere lengths and recorded early fledging and mortality events. At nests with the highest levels of infestation, nestlings had significantly lower mass and haematocrit. In addition, highly parasitized nestlings had corticosterone concentrations twice as high on average (42.9 ng/ml) than non-parasitized nestlings (20.2 ng/ml). Telomeres of highly parasitized female nestlings significantly shortened as eagles aged, but we found no effect of parasitism on the telomeres of male nestlings. Finally, in nests with higher infestation levels, eagle nestlings were 20 times more likely to die, often because they left the nest before they could fly. These results suggest that H. inodorus may limit local golden eagle populations by decreasing productivity. For eagles that survived infestation, chronically elevated glucocorticoids and shortened telomeres may adversely affect cognitive function or survival in this otherwise long-lived species. Emerging threats from ectoparasites should be an important management consideration for protected species, like golden eagles.

Fragmentation of Apolipoprotein E4 is Required for Differential Expression of Inflammation and Activation Related Genes in Microglia Cells.

The apolipoprotein E4 (APOE4) allele represents the single greatest risk factor for late-onset Alzheimer's disease (AD) and accumulating evidence suggests that fragmentation with a toxic-gain of function may be a key molecular step associated with this risk. Recently, we demonstrated strong immunoreactivity of a 151 amino-terminal fragment of apoE4 (E4-fragment) within the nucleus of microglia in the human AD brain. In vitro, this fragment led to toxicity and activation of inflammatory processes in BV2 microglia cells. Additionally, a transcriptome analysis following exogenous treatment of BV2 microglia cells with this E4 fragment led to a > 2-fold up regulation of 1,608 genes, with many genes playing a role in inflammation and microglia activation. To extend these findings, we here report a similar transcriptome analysis in BV2 microglia cells following treatment with full-length ApoE4 (FL-ApoE4). The results indicated that full-length ApoE4 had a very small effect on gene expression compared to the fragment. Only 48 differentially expressed genes (DEGs) were identified (p < 0.05, and greater than 2-fold change). A gene ontology analysis of these DEGs indicated that they are not involved in inflammatory and activation processes, in contrast to the genes up regulated by the E4-fragment. In addition, genes that showed a negative fold-change upon FL-E4 treatment typically showed a strong positive fold-change upon treatment with the fragment (Pearson's r = -0.7). Taken together, these results support the hypothesis that a key step in the conversion of microglia to an activated phenotype is proteolytic cleavage of FL-ApoE4. Therefore, the neutralization of this amino-terminal fragment of ApoE4, specifically, may serve as an important therapeutic strategy in the treatment of AD.