Emergent properties as by-products of prebiotic evolution of aminoacylation ribozymes.

Systems of catalytic RNAs presumably gave rise to important evolutionary innovations, such as the genetic code. Such systems may exhibit particular tolerance to errors (error minimization) as well as coding specificity. While often assumed to result from natural selection, error minimization may instead be an emergent by-product. In an RNA world, a system of self-aminoacylating ribozymes could enforce the mapping of amino acids to anticodons. We measured the activity of thousands of ribozyme mutants on alternative substrates (activated analogs for tryptophan, phenylalanine, leucine, isoleucine, valine, and methionine). Related ribozymes exhibited shared preferences for substrates, indicating that adoption of additional amino acids by existing ribozymes would itself lead to error minimization. Furthermore, ribozyme activity was positively correlated with specificity, indicating that selection for increased activity would also lead to increased specificity. These results demonstrate that by-products of ribozyme evolution could lead to adaptive value in specificity and error tolerance.

Kinetic sequencing (k-Seq) as a massively parallel assay for ribozyme kinetics: utility and critical parameters.

Characterizing genotype-phenotype relationships of biomolecules (e.g. ribozymes) requires accurate ways to measure activity for a large set of molecules. Kinetic measurement using high-throughput sequencing (e.g. k-Seq) is an emerging assay applicable in various domains that potentially scales up measurement throughput to over 106 unique nucleic acid sequences. However, maximizing the return of such assays requires understanding the technical challenges introduced by sequence heterogeneity and DNA sequencing. We characterized the k-Seq method in terms of model identifiability, effects of sequencing error, accuracy and precision using simulated datasets and experimental data from a variant pool constructed from previously identified ribozymes. Relative abundance, kinetic coefficients, and measurement noise were found to affect the measurement of each sequence. We introduced bootstrapping to robustly quantify the uncertainty in estimating model parameters and proposed interpretable metrics to quantify model identifiability. These efforts enabled the rigorous reporting of data quality for individual sequences in k-Seq experiments. Here we present detailed protocols, define critical experimental factors, and identify general guidelines to maximize the number of sequences and their measurement accuracy from k-Seq data. Analogous practices could be applied to improve the rigor of other sequencing-based assays.

Promiscuous Ribozymes and Their Proposed Role in Prebiotic Evolution.

The ability of enzymes, including ribozymes, to catalyze side reactions is believed to be essential to the evolution of novel biochemical activities. It has been speculated that the earliest ribozymes, whose emergence marked the origin of life, were low in activity but high in promiscuity, and that these early ribozymes gave rise to specialized descendants with higher activity and specificity. Here, we review the concepts related to promiscuity and examine several cases of highly promiscuous ribozymes. We consider the evidence bearing on the question of whether de novo ribozymes would be quantitatively more promiscuous than later evolved ribozymes or protein enzymes. We suggest that while de novo ribozymes appear to be promiscuous in general, they are not obviously more promiscuous than more highly evolved or active sequences. Promiscuity is a trait whose value would depend on selective pressures, even during prebiotic evolution.

Mapping a Systematic Ribozyme Fitness Landscape Reveals a Frustrated Evolutionary Network for Self-Aminoacylating RNA.

Molecular evolution can be conceptualized as a walk over a "fitness landscape", or the function of fitness (e.g., catalytic activity) over the space of all possible sequences. Understanding evolution requires knowing the structure of the fitness landscape and identifying the viable evolutionary pathways through the landscape. However, the fitness landscape for any catalytic biomolecule is largely unknown. The evolution of catalytic RNA is of special interest because RNA is believed to have been foundational to early life. In particular, an essential activity leading to the genetic code would be the reaction of ribozymes with activated amino acids, such as 5(4 H)-oxazolones, to form aminoacyl-RNA. Here we combine in vitro selection with a massively parallel kinetic assay to map a fitness landscape for self-aminoacylating RNA, with nearly complete coverage of sequence space in a central 21-nucleotide region. The method (SCAPE: sequencing to measure catalytic activity paired with in vitro evolution) shows that the landscape contains three major ribozyme families (landscape peaks). An analysis of evolutionary pathways shows that, while local optimization within a ribozyme family would be possible, optimization of activity over the entire landscape would be frustrated by large valleys of low activity. The sequence motifs associated with each peak represent different solutions to the problem of catalysis, so the inability to traverse the landscape globally corresponds to an inability to restructure the ribozyme without losing activity. The frustrated nature of the evolutionary network suggests that chance emergence of a ribozyme motif would be more important than optimization by natural selection.

Molecular Fitness Landscapes from High-Coverage Sequence Profiling.

The function of fitness (or molecular activity) in the space of all possible sequences is known as the fitness landscape. Evolution is a random walk on the fitness landscape, with a bias toward climbing hills. Mapping the topography of real fitness landscapes is fundamental to understanding evolution, but previous efforts were hampered by the difficulty of obtaining large, quantitative data sets. The accessibility of high-throughput sequencing (HTS) has transformed this study, enabling large-scale enumeration of fitness for many mutants and even complete sequence spaces in some cases. We review the progress of high-throughput studies in mapping molecular fitness landscapes, both in vitro and in vivo, as well as opportunities for future research. Such studies are rapidly growing in number. HTS is expected to have a profound effect on the understanding of real molecular fitness landscapes.

Asymmetric Mbc, active Rac1 and F-actin foci in the fusion-competent myoblasts during myoblast fusion in Drosophila.

Myoblast fusion is an intricate process that is initiated by cell recognition and adhesion, and culminates in cell membrane breakdown and formation of multinucleate syncytia. In the Drosophila embryo, this process occurs asymmetrically between founder cells that pattern the musculature and fusion-competent myoblasts (FCMs) that account for the bulk of the myoblasts. The present studies clarify and amplify current models of myoblast fusion in several important ways. We demonstrate that the non-conventional guanine nucleotide exchange factor (GEF) Mbc plays a fundamental role in the FCMs, where it functions to activate Rac1, but is not required in the founder cells for fusion. Mbc, active Rac1 and F-actin foci are highly enriched in the FCMs, where they localize to the Sns:Kirre junction. Furthermore, Mbc is crucial for the integrity of the F-actin foci and the FCM cytoskeleton, presumably via its activation of Rac1 in these cells. Finally, the local asymmetric distribution of these proteins at adhesion sites is reminiscent of invasive podosomes and, consistent with this model, they are enriched at sites of membrane deformation, where the FCM protrudes into the founder cell/myotube. These data are consistent with models promoting actin polymerization as the driving force for myoblast fusion.