Synthetic shuffling and in vitro selection reveal the rugged adaptive fitness landscape of a kinase ribozyme

Abstract

The relationship between genotype and phenotype is often described as an adaptive fitness landscape. In this study, we used a combination of recombination, in vitro selection, and comparative sequence analysis to characterize the fitness landscape of a previously isolated kinase ribozyme. Point mutations present in improved variants of this ribozyme were recombined in vitro in more than 10 14 different arrangements using synthetic shuffling, and active variants were isolated by in vitro selection. Mutual information analysis of 65 recombinant ribozymes isolated in the selection revealed a rugged fitness landscape in which approximately one-third of the 91 pairs of positions analyzed showed evidence of correlation. Pairs of correlated positions overlapped to form densely connected networks, and groups of maximally connected nucleotides occurred significantly more often in these networks than they did in randomized control networks with the same number of links. The activity of the most efficient recombinant ribozyme isolated from the synthetically shuffled pool was 30-fold greater than that of any of the ribozymes used to build it, which indicates that synthetic shuffling can be a rich source of ribozyme variants with improved properties.

Elucidating the molecular architecture of adaptation via evolve and resequence experiments

“…NGS allows testing the selected population in earlier rounds and provides a much more complete picture of the final array of winning genotypes 44 . In fact, direct experimental measurement of the fitness landscapes of RNA ligase 15 , kinase 45 , Diels-Alderase 46 , and self-splicing ribozymes 47 are obtained at much higher resolution than ever before. Combined with microfluidic analytical platforms, NGS can be directly coupled to activity measurement, revealing the fitness landscape of a functional RNA 48,49 .…”

“…In one example, selection for GTP aptamers directly yielded an optimal family of aptamer sequences, suggesting that these sequences were present in the initial pool; by contrast, other aptamer families improved their binding affinity by several orders of magnitude upon mutagenesis and re-selection, suggesting that the initial sequences of these aptamers were relatively far from optimal and required subsequent newly arising mutations for optimal activity 35,77 . To date, the evidence from NGS of in vitro selected pools suggest that individual families of functional RNAs exist in the starting pools, but greatly benefit from mutagenesis 15,46,77 or synthetic shuffling 45 to uncover the most active variants, which then do not tend to drift towards other peaks in the fitness landscape 78 .…”

Topological features of rugged fitness landscapes in sequence space

“…However, even when the issue of a changing environment is ignored (readers are referred to [5] for a detailed model of a fitness landscape affected by environmental change), as we do for the purpose of this review, substantial challenges remain when charting the fitness landscapes of genomes of any appreciable size. First, the number of all possible genotypes (or sequence space) is beyond our theoretical computational capacity even for a single protein sequence, although attempts to explore larger volumes of sequence space are being reported for proteins [6][7][8] and small RNA molecules [9][10][11]. Second, we typically obtain sequence data from extant organisms and, therefore, we chart the sequence landscape from a biased set of sequences that mostly correspond to genotypes conferring high fitness.…”

Altered biochemical specificity of G-quadruplexes with mutated tetrads

“…Answering this important question could be facilitated by bioinformatic methods capable of identifying the examples in sequenced genomes most likely to be functional. An approach widely used to address this issue for nucleic acid motifs with conventional duplex structures is comparative sequence analysis (Figure 1) (31–35). This method is based in part on the observation that mutational changes at certain positions in sequence alignments of conserved nucleic acid secondary structures typically occur only in the presence of specific mutational changes at a second position in the alignment (Figure 1B).…”