Next-generation sequencing reveals how RNA catalysts evolve from random space

Fitness Landscapes and Evolution of Catalytic RNA

The relationship between genotype and phenotype, or the fitness landscape, is the foundation of genetic engineering and evolution. However, mapping fitness landscapes poses a major technical challenge due to the amount of quantifiable data that is required. Catalytic RNA is a special topic in the study of fitness landscapes due to its relatively small sequence space combined with its importance in synthetic biology. The combination of in vitro selection and high-throughput sequencing has recently provided empirical maps of both complete and local RNA fitness landscapes, but the astronomical size of sequence space limits purely experimental investigations. Next steps are likely to involve data-driven interpolation and extrapolation over sequence space using various machine learning techniques. We discuss recent progress in understanding RNA fitness landscapes, particularly with respect to protocells and machine representations of RNA. The confluence of technical advances may significantly impact synthetic biology in the near future.

Generating experimentally unrelated target molecule-binding highly functionalized nucleic-acid polymers using machine learning

In vitro selection queries large combinatorial libraries for sequence-defined polymers with target binding and reaction catalysis activity. While the total sequence space of these libraries can extend beyond 10²² sequences, practical considerations limit starting sequences to ≤~10¹⁵ distinct molecules. Selection-induced sequence convergence and limited sequencing depth further constrain experimentally observable sequence space. To address these limitations, we integrate experimental and machine learning approaches to explore regions of sequence space unrelated to experimentally derived variants. We perform in vitro selections to discover highly side-chain-functionalized nucleic acid polymers (HFNAPs) with potent affinities for a target small molecule (daunomycin K_D = 5-65 nM). We then use the selection data to train a conditional variational autoencoder (CVAE) machine learning model to generate diverse and unique HFNAP sequences with high daunomycin affinities (K_D = 9-26 nM), even though they are unrelated in sequence to experimental polymers. Coupling in vitro selection with a machine learning model thus enables direct generation of active variants, demonstrating a new approach to the discovery of functional biopolymers.

High-Throughput Activity Profiling of RNA-Cleaving DNA Catalysts by Deoxyribozyme Sequencing (DZ-seq)

RNA-cleaving deoxyribozymes have found broad application as useful tools for RNA biochemistry. However, tedious in vitro selection procedures combined with laborious characterization of individual candidate catalysts hinder the discovery of novel catalytic motifs. Here, we present a new high-throughput sequencing method, DZ-seq, which directly measures activity and localizes cleavage sites of thousands of deoxyribozymes. DZ-seq exploits A-tailing followed by reverse transcription with an oligo-dT primer to capture the cleavage status and sequences of both deoxyribozyme and RNA substrate. We validated DZ-seq by conventional analytical methods and demonstrated its utility by discovery of novel deoxyribozymes that allow for cleaving challenging RNA targets or the analysis of RNA modification states.

Self-Reproduction and Darwinian Evolution in Autocatalytic Chemical Reaction Systems

Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as "a self-sustaining chemical system capable of Darwinian evolution". It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.

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.

Comprehensive sequence-to-function mapping of cofactor-dependent RNA catalysis in the glmS ribozyme

Massively parallel, quantitative measurements of biomolecular activity across sequence space can greatly expand our understanding of RNA sequence-function relationships. We report the development of an RNA-array assay to perform such measurements and its application to a model RNA: the core glmS ribozyme riboswitch, which performs a ligand-dependent self-cleavage reaction. We measure the cleavage rates for all possible single and double mutants of this ribozyme across a series of ligand concentrations, determining kcat and KM values for active variants. These systematic measurements suggest that evolutionary conservation in the consensus sequence is driven by maintenance of the cleavage rate. Analysis of double-mutant rates and associated mutational interactions produces a structural and functional mapping of the ribozyme sequence, revealing the catalytic consequences of specific tertiary interactions, and allowing us to infer structural rearrangements that permit certain sequence variants to maintain activity.

Systematic minimization of RNA ligase ribozyme through large-scale design-synthesis-sequence cycles

Template-directed RNA ligation catalyzed by an RNA enzyme (ribozyme) is a plausible and important reaction that could have been involved in transferring genetic information during prebiotic evolution. Laboratory evolution experiments have yielded several classes of ligase ribozymes, but their minimal sequence requirements remain largely unexplored. Because selection experiments strongly favor highly active sequences, less active but smaller catalytic motifs may have been overlooked in these experiments. We used large-scale DNA synthesis and high-throughput ribozyme assay enabled by deep sequencing to systematically minimize a previously laboratory-evolved ligase ribozyme. After designing and evaluating >10 000 sequences, we identified catalytic cores as small as 18 contiguous bases that catalyze template-directed regiospecific RNA ligation. The fact that such a short sequence can catalyze this critical reaction suggests that similarly simple or even simpler motifs may populate the RNA sequence space which could have been accessible to the prebiotic ribozymes.

A Novel Small RNA-Cleaving Deoxyribozyme with a Short Binding Arm

Deoxyribozymes capable of catalyzing sequence-specific RNA cleavage have found broad applications in biotechnology, DNA computing and environmental sensing. Among these, deoxyribozyme 8–17 is the most common small DNA motif capable of catalyzing RNA cleavage. However, the extent to which other DNA molecules with similar catalytic motifs exist remains elusive. Here we report a novel RNA-cleaving deoxyribozyme called 10–12opt that functions with an equally small catalytic motif and an unusually short binding arm. This deoxyribozyme contains a 14-nucleotide catalytic core that preferentially catalyzes RNA cleavage at UN dinucleotide junctions (k_obs = 0.9 h⁻¹ for UU cleavage). Surprisingly, the left binding arm contains only three nucleotides and forms two canonical base pairs with the RNA substrate. Mutational analysis reveals that a riboguanosine residue 3-nucleotide downstream of cleavage site must not form canonical base pairing for the optimal catalysis, and this nucleobase likely participates in catalysis with its carbonyl O6 atom. Furthermore, we demonstrate that deoxyribozyme 10–12opt can be utilized to cleave certain microRNA sequences which are not preferentially cleaved by 8–17. Together, these results suggest that this novel RNA-cleaving deoxyribozyme forms a distinct catalytic structure than 8–17 and that sequence space may contain additional examples of DNA molecules that can cleave RNA at site-specific locations.

Optimization of fluorogenic RNA-based biosensors using droplet-based microfluidic ultrahigh-throughput screening

Biosensors are biological molecules able to detect and report the presence of a target molecule by the emission of a signal. Nucleic acids are particularly appealing for the design of such molecule since their great structural plasticity makes them able to specifically interact with a wide range of ligands and their structure can rearrange upon recognition to trigger a reporting event. A biosensor is typically made of three main domains: a sensing domain that is connected to a reporting domain via a communication module in charge of transmitting the sensing event through the molecule. The communication module is therefore an instrumental element of the sensor. This module is usually empirically developed through a trial-and-error strategy with the testing of only a few combinations judged relevant by the experimenter. In this work, we introduce a novel method combining the use of droplet-based microfluidics and next generation sequencing. This method allows to functionally characterize up to a million of different sequences in a single set of experiments and, by doing so, to exhaustively test every possible sequence permutations of the communication module. Here, we demonstrate the efficiency of the approach by isolating a set of optimized RNA biosensors able to sense theophylline and to convert this recognition into fluorescence emission.

High-throughput methods in aptamer discovery and analysis

Aptamers are small, functional nucleic acids that bind a variety of targets, often with high specificity and affinity. Genomic aptamers constitute the ligand-binding domains of riboswitches, whereas synthetic aptamers find applications as diagnostic and therapeutic tools, and as ligand-binding domains of regulatory RNAs in synthetic biology. Discovery and characterization of aptamers has been limited by a lack of high-throughput approaches that uncover the target-binding domains and the biochemical properties of individual sequences. With the advent of high-throughput sequencing, large-scale analysis of in vitro selected populations of aptamers (and catalytic nucleic acids, such as ribozymes and DNAzmes) became possible. In recent years the development of new experimental approaches and software tools has led to significant streamlining of the selection-pool analysis. This article provides an overview of post-selection data analysis and describes high-throughput methods that facilitate rapid discovery and biochemical characterization of aptamers.

Applications of high-throughput sequencing to analyze and engineer ribozymes

A large number of catalytic RNAs, or ribozymes, have been identified in the genomes of various organisms and viruses. Ribozymes are involved in biological processes such as regulation of gene expression and viral replication, but biological roles of many ribozymes still remain unknown. Ribozymes have also inspired researchers to engineer synthetic ribozymes that function as sensors or gene switches. To gain deeper understanding of the sequence-function relationship of ribozymes and to efficiently engineer synthetic ribozymes, a large number of ribozyme variants need to be examined which was limited to hundreds of sequences by Sanger sequencing. The advent of high-throughput sequencing technologies, however, has allowed us to sequence millions of ribozyme sequences at low cost. This review focuses on the recent applications of high-throughput sequencing to both characterize and engineer ribozymes, to highlight how the large-scale sequence data can advance ribozyme research and engineering.

Nucleic acids: function and potential for abiogenesis

The emergence of functional cooperation between the three main classes of biomolecules - nucleic acids, peptides and lipids - defines life at the molecular level. However, how such mutually interdependent molecular systems emerged from prebiotic chemistry remains a mystery. A key hypothesis, formulated by Crick, Orgel and Woese over 40 year ago, posits that early life must have been simpler. Specifically, it proposed that an early primordial biology lacked proteins and DNA but instead relied on RNA as the key biopolymer responsible not just for genetic information storage and propagation, but also for catalysis, i.e. metabolism. Indeed, there is compelling evidence for such an 'RNA world', notably in the structure of the ribosome as a likely molecular fossil from that time. Nevertheless, one might justifiably ask whether RNA alone would be up to the task. From a purely chemical perspective, RNA is a molecule of rather uniform composition with all four bases comprising organic heterocycles of similar size and comparable polarity and pK a values. Thus, RNA molecules cover a much narrower range of steric, electronic and physicochemical properties than, e.g. the 20 amino acid side-chains of proteins. Herein we will examine the functional potential of RNA (and other nucleic acids) with respect to self-replication, catalysis and assembly into simple protocellular entities.

Large Scale Mutational and Kinetic Analysis of a Self-Hydrolyzing Deoxyribozyme

Deoxyribozymes are catalytic DNA sequences whose atomic structures are generally difficult to elucidate. Mutational analysis remains a principal approach for understanding and engineering deoxyribozymes with diverse catalytic activities. However, laborious preparation and biochemical characterization of individual sequences severely limit the number of mutants that can be studied biochemically. Here, we applied deep sequencing to directly measure the activities of self-hydrolyzing deoxyribozyme sequences in high throughput. First, all single and double mutants within the 15-base catalytic core of the deoxyribozyme I-R3 were assayed to unambiguously determine the tolerated and untolerated mutations at each position. Subsequently, 4096 deoxyribozyme variants with tolerated base substitutions at seven positions were kinetically assayed in parallel. We identified 533 active mutants whose first-order rate constants and activation energies were determined. The results indicate an isolated and narrow peak in the deoxyribozyme sequence space and provide a quantitative view of the effects of multiple mutations on the deoxyribozyme activity for the first time.

Analysis of in vitro evolution reveals the underlying distribution of catalytic activity among random sequences

The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher's Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the distribution of fitness and activity in the random sequence pool for the first time. The frequency distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions.

Heterodimerization of Group I Ribozymes Enabling Exon Recombination through Pairs of Cooperative trans-Splicing Reactions

Group I (GI) self-splicing ribozymes are attractive tools for biotechnology and synthetic biology. Several trans-splicing and related reactions based on GI ribozymes have been developed for the purpose of recombining their target mRNA sequences. By combining trans-splicing systems with rational modular engineering of GI ribozymes it was possible to achieve more complex editing of target RNA sequences. In this study we have developed a cooperative trans-splicing system through rational modular engineering with use of dimeric GI ribozymes derived from the Tetrahymena group I intron ribozyme. The resulting pairs of ribozymes exhibited catalytic activity depending on their selective dimerization. Rational modular redesign as performed in this study would facilitate the development of sophisticated regulation of double or multiple trans-splicing reactions in a cooperative manner.

Recognizing RNA structural motifs in HT-SELEX data for ribosomal protein S15

BACKGROUND

Proteins recognize many different aspects of RNA ranging from single stranded regions to discrete secondary or tertiary structures. High-throughput sequencing (HTS) of in vitro selected populations offers a large scale method to study RNA-proteins interactions. However, most existing analysis methods require that the binding motifs are enriched in the population relative to earlier rounds, and that motifs are found in a loop or single stranded region of the potential RNA secondary structure. Such methods do not generalize to all RNA-protein interaction as some RNA binding proteins specifically recognize more complex structures such as double stranded RNA.

RESULTS

In this study, we use HT-SELEX derived populations to study the landscape of RNAs that interact with Geobacillus kaustophilus ribosomal protein S15. Our data show high sequence and structure diversity and proved intractable to existing methods. Conventional programs identified some sequence motifs, but these are found in less than 5-10% of the total sequence pool. Therefore, we developed a novel framework to analyze HT-SELEX data. Our process accounts for both sequence and structure components by abstracting the overall secondary structure into smaller substructures composed of a single base-pair stack, which allows us to leverage existing approaches already used in k-mer analysis to identify enriched motifs. By focusing on secondary structure motifs composed of specific two base-pair stacks, we identified significantly enriched or depleted structure motifs relative to earlier rounds.

CONCLUSIONS

Discrete substructures are likely to be important to RNA-protein interactions, but they are difficult to elucidate. Substructures can help make highly diverse sequence data more tractable. The structure motifs provide limited accuracy in predicting enrichment suggesting that G. kaustophilus S15 can either recognize many different secondary structure motifs or some aspects of the interaction are not captured by the analysis. This highlights the importance of considering secondary and tertiary structure elements and their role in RNA-protein interactions.

Synthetic, Switchable Enzymes

The construction of switchable, radiation-controlled, aptameric enzymes - "swenzymes" - is, in principle, feasible. We propose a strategy to make such catalysts from 2 (or more) aptamers each selected to bind specifically to one of the substrates in, for example, a 2-substrate reaction. Construction of a combinatorial library of candidate swenzymes entails selecting a set of a million aptamers that bind one substrate and a second set of a million aptamers that bind the second substrate; the aptamers in these sets are then linked pairwise by a linker, thus bringing together the substrates. In the presence of the substrates, some linked aptamer pairs catalyze the reaction when exposed to external energy in the form of a specific frequency of low-intensity, nonionizing electromagnetic or acoustic radiation. Such swenzymes are detected via a separate product-capturing aptamer that changes conformation on capturing the product; this altered conformation allows it (1) to bind to every potential swenzyme in its vicinity (thereby giving a higher probability of capture to the swenzymes that generate the product) and (2) to bind to a sequence on a magnetic bead (thereby permitting purification of the swenzyme plus product-capturing aptamer by precipitation). Attempts to implement the swenzyme strategy may help elucidate fundamental problems in enzyme catalysis.

Viroid quasispecies revealed by deep sequencing

Viroids are non-coding single-stranded circular RNA molecules that replicate autonomously in infected host plants causing mild to lethal symptoms. Their genomes contain about 250-400 nucleotides, depending on viroid species. Members of the family Pospiviroidae, like the Potato spindle tuber viroid (PSTVd), replicate via an asymmetric rolling-circle mechanism using the host DNA-dependent RNA-Polymerase II in the nucleus, while members of Avsunviroidae are replicated in a symmetric rolling-circle mechanism probably by the nuclear-encoded polymerase in chloroplasts. Viroids induce the production of viroid-specific small RNAs (vsRNA) that can direct (post-)transcriptional gene silencing against host transcripts or genomic sequences. Here, we used deep-sequencing to analyze vsRNAs from plants infected with different PSTVd variants to elucidate the PSTVd quasipecies evolved during infection. We recovered several novel as well as previously known PSTVd variants that were obviously competent in replication and identified common strand-specific mutations. The calculated mean error rate per nucleotide position was less than [Formula: see text], quite comparable to the value of [Formula: see text] reported for a member of Avsunviroidae. The resulting error threshold allows the synthesis of longer-than-unit-length replication intermediates as required by the asymmetric rolling-circle mechanism of members of Pospiviroidae.

High-Throughput Mutational Analysis of a Twister Ribozyme

Recent discoveries of new classes of self‐cleaving ribozymes in diverse organisms have triggered renewed interest in the chemistry and biology of ribozymes. Functional analysis and engineering of ribozymes often involve performing biochemical assays on multiple ribozyme mutants. However, because each ribozyme mutant must be individually prepared and assayed, the number and variety of mutants that can be studied are severely limited. All of the single and double mutants of a twister ribozyme (a total of 10 296 mutants) were generated and assayed for their self‐cleaving activity by exploiting deep sequencing to count the numbers of cleaved and uncleaved sequences for every mutant. Interestingly, we found that the ribozyme is highly robust against mutations such that 71 % and 30 % of all single and double mutants, respectively, retain detectable activity under the assay conditions. It was also observed that the structural elements that comprise the ribozyme exhibit distinct sensitivity to mutations.

The in vitro selection world

Through iterative cycles of selection, amplification, and mutagenesis, in vitro selection provides the ability to isolate molecules of desired properties and function from large pools (libraries) of random molecules with as many as 10(16) distinct species. This review, in recognition of a quarter of century of scientific discoveries made through in vitro selection, starts with a brief overview of the method and its history. It further covers recent developments in in vitro selection with a focus on tools that enhance the capabilities of in vitro selection and its expansion from being purely a nucleic acids selection to that of polypeptides and proteins. In addition, we cover how next generation sequencing and modern biological computational tools are being used to complement in vitro selection experiments. On the very least, sequencing and computational tools can translate the large volume of information associated with in vitro selection experiments to manageable, analyzable, and exploitable information. Finally, in vivo selection is briefly compared and contrasted to in vitro selection to highlight the unique capabilities of each method.

Searching for a DNAzyme Version of the Leadzyme

The leadzyme refers to a small ribozyme that cleaves a RNA substrate in the presence of Pb(2+). In an optimized form, the enzyme strand contains only two unpaired nucleotides. Most RNA-cleaving DNAzymes are much longer. Two classical Pb(2+)-dependent DNAzymes, 8-17 and GR5, both contain around 15 nucleotides in the enzyme loop. This is also the size of most RNA-cleaving DNAzymes that use other metal ions for their activity. Such large enzyme loops make spectroscopic characterization difficult and so far no high-resolution structural information is available for active DNAzymes. The goal of this work is to search for DNAzymes with smaller enzyme loops. A simple replacement of the ribonucleotides in the leadzyme by deoxyribonucleotides failed to produce an active enzyme. A Pb(2+)-dependent in vitro selection combined with deep sequencing was then performed. After sequence alignment and DNA folding, a new DNAzyme named PbE22 was identified, which contains only 5 nucleotides in the enzyme catalytic loop. The biochemical characteristics of PbE22 were compared with those of the leadzyme and the two classical Pb(2+)-dependent DNAzymes. The rate of PbE22 rises with increase in Pb(2+) concentration, being 1.7 h(-1) in the presence of 100 μM Pb(2+) and reaching 3.5 h(-1) at 500 µM Pb(2+). The log of PbE22 rate rises linearly in a pH-dependent fashion (20 µM Pb(2+)) with a slope of 0.74. In addition, many other abundant sequences in the final library were studied. These sequences are quite varied in length and nucleotide composition, but some contain a few conserved nucleotides consistent with the GR5 structure. Interestingly, some sequences are active with Pb(2+) but none of them were active with even 50 mM Mg(2+), which is reminiscent of the difference between the GR5 and 8-17 DNAzymes.

Elucidating the molecular architecture of adaptation via evolve and resequence experiments

Evolve and resequence (E&R) experiments use experimental evolution to adapt populations to a novel environment, then next-generation sequencing to analyse genetic changes. They enable molecular evolution to be monitored in real time on a genome-wide scale. Here, we review the field of E&R experiments across diverse systems, ranging from simple non-living RNA to bacteria, yeast and the complex multicellular organism Drosophila melanogaster. We explore how different evolutionary outcomes in these systems are largely consistent with common population genetics principles. Differences in outcomes across systems are largely explained by different starting population sizes, levels of pre-existing genetic variation, recombination rates and adaptive landscapes. We highlight emerging themes and inconsistencies that future experiments must address.

Fitness Landscapes of Functional RNAs

The notion of fitness landscapes, a map between genotype and fitness, was proposed more than 80 years ago. For most of this time data was only available for a few alleles, and thus we had only a restricted view of the whole fitness landscape. Recently, advances in genetics and molecular biology allow a more detailed view of them. Here we review experimental and theoretical studies of fitness landscapes of functional RNAs, especially aptamers and ribozymes. We find that RNA structures can be divided into critical structures, connecting structures, neutral structures and forbidden structures. Such characterisation, coupled with theoretical sequence-to-structure predictions, allows us to construct the whole fitness landscape. Fitness landscapes then can be used to study evolution, and in our case the development of the RNA world.

In vitro evolution of distinct self-cleaving ribozymes in diverse environments

In vitro evolution experiments have long been used to evaluate the roles of RNA in both modern and ancient biology, and as a tool for biotechnology applications. The conditions under which these experiments have been conducted, however, do not reflect the range of cellular environments in modern biology or our understanding of chemical environments on the early earth, when the atmosphere and oceans were largely anoxic and soluble Fe²⁺ was abundant. To test the impact of environmental factors relevant to RNA's potential role in the earliest forms of life, we evolved populations of self-cleaving ribozymes in an anoxic atmosphere with varying pH in the presence of either Fe²⁺ or Mg²⁺. Populations evolved under these different conditions are dominated by different sequences and secondary structures, demonstrating global differences in the underlying fitness landscapes. Comparisons between evolutionary outcomes and catalytic activities also indicate that Mg²⁺ can readily take the place of Fe²⁺ in supporting the catalysis of RNA cleavage at neutral pH, but not at lower pH. These results highlight the importance of considering the specific environments in which functional biopolymers evolve when evaluating their potential roles in the origin of life, extant biology, or biotechnology.

High-throughput assay and engineering of self-cleaving ribozymes by sequencing

Self-cleaving ribozymes are found in all domains of life and are believed to play important roles in biology. Additionally, self-cleaving ribozymes have been the subject of extensive engineering efforts for applications in synthetic biology. These studies often involve laborious assays of multiple individual variants that are either designed rationally or discovered through selection or screening. However, these assays provide only a limited view of the large sequence space relevant to the ribozyme function. Here, we report a strategy that allows quantitative characterization of greater than 1000 ribozyme variants in a single experiment. We generated a library of predefined ribozyme variants that were converted to DNA and analyzed by high-throughput sequencing. By counting the number of cleaved and uncleaved reads of every variant in the library, we obtained a complete activity profile of the ribozyme pool which was used to both analyze and engineer allosteric ribozymes.

FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections

High-throughput sequence (HTS) analysis of combinatorial selection populations accelerates lead discovery and optimization and offers dynamic insight into selection processes. An underlying principle is that selection enriches high-fitness sequences as a fraction of the population, whereas low-fitness sequences are depleted. HTS analysis readily provides the requisite numerical information by tracking the evolutionary trajectory of individual sequences in response to selection pressures. Unlike genomic data, for which a number of software solutions exist, user-friendly tools are not readily available for the combinatorial selections field, leading many users to create custom software. FASTAptamer was designed to address the sequence-level analysis needs of the field. The open source FASTAptamer toolkit counts, normalizes and ranks read counts in a FASTQ file, compares populations for sequence distribution, generates clusters of sequence families, calculates fold-enrichment of sequences throughout the course of a selection and searches for degenerate sequence motifs. While originally designed for aptamer selections, FASTAptamer can be applied to any selection strategy that can utilize next-generation DNA sequencing, such as ribozyme or deoxyribozyme selections, in vivo mutagenesis and various surface display technologies (peptide, antibody fragment, mRNA, etc.). FASTAptamer software, sample data and a user's guide are available for download at http://burkelab.missouri.edu/fastaptamer.html.

Broccoli: rapid selection of an RNA mimic of green fluorescent protein by fluorescence-based selection and directed evolution

Genetically encoded fluorescent ribonucleic acids (RNAs) have diverse applications, including imaging RNA trafficking and as a component of RNA-based sensors that exhibit fluorescence upon binding small molecules in live cells. These RNAs include the Spinach and Spinach2 aptamers, which bind and activate the fluorescence of fluorophores similar to that found in green fluorescent protein. Although additional highly fluorescent RNA–fluorophore complexes would extend the utility of this technology, the identification of novel RNA–fluorophore complexes is difficult. Current approaches select aptamers on the basis of their ability to bind fluorophores, even though fluorophore binding alone is not sufficient to activate fluorescence. Additionally, aptamers require extensive mutagenesis to efficiently fold and exhibit fluorescence in living cells. Here we describe a platform for rapid generation of highly fluorescent RNA–fluorophore complexes that are optimized for function in cells. This procedure involves selection of aptamers on the basis of their binding to fluorophores, coupled with fluorescence-activated cell sorting (FACS) of millions of aptamers expressed in Escherichia coli. Promising aptamers are then further optimized using a FACS-based directed evolution approach. Using this approach, we identified several novel aptamers, including a 49-nt aptamer, Broccoli. Broccoli binds and activates the fluorescence of (Z)-4-(3,5-difluoro-4-hydroxybenzylidene)-1,2-dimethyl-1H-imidazol-5(4H)-one. Broccoli shows robust folding and green fluorescence in cells, and increased fluorescence relative to Spinach2. This reflects, in part, improved folding in the presence of low cytosolic magnesium concentrations. Thus, this novel fluorescence-based selection approach simplifies the generation of aptamers that are optimized for expression and performance in living cells.

A synthetic approach to abiogenesis

Synthetic biology seeks to probe fundamental aspects of biological form and function by construction (resynthesis) rather than deconstruction (analysis). Here we discuss how such an approach could be applied to assemble synthetic quasibiological systems able to replicate and evolve, illuminating universal properties of life and the search for its origins.