The genetic code constrains yet facilitates Darwinian evolution

Nucleic acid recognition during prokaryotic immunity

Parasitic elements often spread to hosts through the delivery of their nucleic acids to the recipient. This is particularly true for the primary parasites of bacteria, bacteriophages (phages) and plasmids. Although bacterial immune systems can sense a diverse set of infection signals, such as a protein unique to the invader or the disruption of natural host processes, phage and plasmid nucleic acids represent some of the most common molecules that are recognized as foreign to initiate defense. In this review, we will discuss the various elements of invader nucleic acids that can be distinguished by bacterial host immune systems as "non-self" and how this signal is relayed to activate an immune response.

Robust genetic codes enhance protein evolvability

The standard genetic code defines the rules of translation for nearly every life form on Earth. It also determines the amino acid changes accessible via single-nucleotide mutations, thus influencing protein evolvability-the ability of mutation to bring forth adaptive variation in protein function. One of the most striking features of the standard genetic code is its robustness to mutation, yet it remains an open question whether such robustness facilitates or frustrates protein evolvability. To answer this question, we use data from massively parallel sequence-to-function assays to construct and analyze 6 empirical adaptive landscapes under hundreds of thousands of rewired genetic codes, including those of codon compression schemes relevant to protein engineering and synthetic biology. We find that robust genetic codes tend to enhance protein evolvability by rendering smooth adaptive landscapes with few peaks, which are readily accessible from throughout sequence space. However, the standard genetic code is rarely exceptional in this regard, because many alternative codes render smoother landscapes than the standard code. By constructing low-dimensional visualizations of these landscapes, which each comprise more than 16 million mRNA sequences, we show that such alternative codes radically alter the topological features of the network of high-fitness genotypes. Whereas the genetic codes that optimize evolvability depend to some extent on the detailed relationship between amino acid sequence and protein function, we also uncover general design principles for engineering nonstandard genetic codes for enhanced and diminished evolvability, which may facilitate directed protein evolution experiments and the bio-containment of synthetic organisms, respectively.

Self-similarity and the maximum entropy principle in the genetic code

This paper addresses the relationship between information and structure of the genetic code. The code has two puzzling anomalies: First, when viewed as 64 sub-cubes of a [Formula: see text] cube, the codons for serine (S) are not contiguous, and there are amino acid codons with zero redundancy, which goes counter to the objective of error correction. To make sense of this, the paper shows that the genetic code must be viewed not only on stereochemical, co-evolution, and error-correction considerations, but also on two additional factors of significance to natural systems, that of an information-theoretic dimensionality of the code data, and the principle of maximum entropy. One implication of non-integer dimensionality associated with data dimensions is self-similarity to different scales, and it is shown that the genetic code does satisfy this property, and it is further shown that the maximum entropy principle operates through the scrambling of the elements in the sense of maximum algorithmic information complexity, generated by an appropriate exponentiation mapping. It is shown that the new considerations and the use of maximum entropy transformation create new constraints that are likely the reasons for the non-uniform codon groups and codons with no redundancy.

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.

Highly Efficient Libraries Design for Saturation Mutagenesis

Saturation mutagenesis is a semi-rational approach for protein engineering where sites are saturated either entirely or partially to include amino acids of interest. We previously reported on a codon compression algorithm, where a set of minimal degenerate codons are selected according to user-defined parameters such as the target organism, type of saturation and usage levels. Here, we communicate an addition to our web tool that considers the distance between the wild-type codon and the library, depending on its purpose. These forms of restricted collections further reduce library size, lowering downstream screening efforts or, in turn, allowing more comprehensive saturation of multiple sites. The library design tool can be accessed via http://www.dynamcc.com/dynamcc_d/.

Graphical Abstract

Predicting Drug Resistance Using Deep Mutational Scanning

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

Accelerating structure-function mapping using the ViVa webtool to mine natural variation

Thousands of sequenced genomes are now publicly available capturing a significant amount of natural variation within plant species; yet, much of these data remain inaccessible to researchers without significant bioinformatics experience. Here, we present a webtool called ViVa (Visualizing Variation) which aims to empower any researcher to take advantage of the amazing genetic resource collected in the Arabidopsis thaliana 1001 Genomes Project (http://1001genomes.org). ViVa facilitates data mining on the gene, gene family, or gene network level. To test the utility and accessibility of ViVa, we assembled a team with a range of expertise within biology and bioinformatics to analyze the natural variation within the well-studied nuclear auxin signaling pathway. Our analysis has provided further confirmation of existing knowledge and has also helped generate new hypotheses regarding this well-studied pathway. These results highlight how natural variation could be used to generate and test hypotheses about less-studied gene families and networks, especially when paired with biochemical and genetic characterization. ViVa is also readily extensible to databases of interspecific genetic variation in plants as well as other organisms, such as the 3,000 Rice Genomes Project ( http://snp-seek.irri.org/) and human genetic variation ( https://www.ncbi.nlm.nih.gov/clinvar/).

Genomic Deoxyxylulose Phosphate Reductoisomerase (DXR) Mutations Conferring Resistance to the Antimalarial Drug Fosmidomycin in E. coli

Sequence to activity mapping technologies are rapidly developing, enabling the generation and isolation of mutations conferring novel phenotypes. Here we used the CRISPR enabled trackable genome engineering (CREATE) technology to investigate the inhibition of the essential ispC gene in its native genomic context in Escherichia coli. We created a full saturation library of 33 sites proximal to the ligand binding pocket and challenged this library with the antimalarial drug fosmidomycin, which targets the ispC gene product, DXR. This selection is especially challenging since it is relatively weak in E. coli, with multiple naturally occurring pathways for resistance. We identified several previously unreported mutations that confer fosmidomycin resistance, in highly conserved sites that also exist in pathogens including the malaria-inducing Plasmodium falciparum. This approach may have implications for the isolation of resistance-conferring mutations and may affect the design of future generations of fosmidomycin-based drugs.

The Standard Genetic Code Facilitates Exploration of the Space of Functional Nucleotide Sequences

The standard genetic code is well known to be optimized for minimizing the phenotypic effects of single-nucleotide substitutions, a property that was likely selected for during the emergence of a universal code. Given the fitness advantage afforded by high standing genetic diversity in a population in a dynamic environment, it is possible that selection to explore a large fraction of the space of functional proteins also occurred. To determine whether selection for such a property played a role during the emergence of the nearly universal standard genetic code, we investigated the number of functional variants of the Escherichia coli PhoQ protein explored at different time scales under translation using different genetic codes. We found that the standard genetic code is highly optimal for exploring a large fraction of the space of functional PhoQ variants at intermediate time scales as compared to random codes. Environmental changes, in response to which genetic diversity in a population provides a fitness advantage, are likely to have occurred at these intermediate time scales. Our results indicate that the ability of the standard code to explore a large fraction of the space of functional sequence variants arises from a balance between robustness and flexibility and is largely independent of the property of the standard code to minimize the phenotypic effects of mutations. We propose that selection to explore a large fraction of the functional sequence space while minimizing the phenotypic effects of mutations contributed toward the emergence of the standard code as the universal genetic code.

Dynamic Management of Codon Compression for Saturation Mutagenesis

Saturation mutagenesis is conveniently located between the two extremes of protein engineering, namely random mutagenesis, and rational design. It involves mutating a confined number of target residues to other amino acids, and hence requires knowledge regarding the sites for mutagenesis, but not their final identity. There are many different strategies for performing and designing such experiments, ranging from simple single degenerate codons to codon collections that code for distinct sets of amino acids. Here, we provide detailed information on the Dynamic Management for Codon Compression (DYNAMCC) approaches that allow us to precisely define the desired amino acid composition to be introduced to a specific target site. DYNAMCC allows us to set usage thresholds and to eliminate undesirable stop and wild-type codons, thus allowing us to control library size and subsequently downstream screening efforts. The DYNAMCC algorithms are free of charge and are implemented in a website for easy access and usage: www.dynamcc.com .

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology.

The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

The Bioactivity of D-/L-Isonucleoside- and 2'-Deoxyinosine-Incorporated Aptamer AS1411s Including DNA Replication/MicroRNA Expression

In this study, chemical modification of 2'-deoxyinosine (2'-dI) and D-/L-isothymidine (D-/L-isoT) was performed on AS1411. They could promote the nucleotide-protein interaction by changing the local conformation. Twenty modified sequences were obtained, FCL-I and FCL-II showed the most noticeable activity improvement. They stabilized the G-quadruplex, remained highly resistant to serum degradation and specificity for nucleolin, further inhibited tumor cell growth, exhibited a stronger ability to influence the different phases of the tumor cell cycle, induced S-phase arrest, promoted the inhibition of DNA replication, and suppressed the unwound function of a large T antigen as powerful as AS1411. The microarray analysis and TaqMan PCR results showed that FCL-II can upregulate the expression of four breast-cancer-related, lowly expressed miRNAs and downregulate the expression of three breast-cancer-related, highly expressed miRNAs (>2.5-fold). FCL-II resulted in enhanced treatment effects greater than AS1411 in animal experiments (p < 0.01). The computational results further proved that FCL-II exhibits more structural advantages than AS1411 for binding to the target protein nucleolin, indicating its great potential in antitumor therapy.

The Resistome: A Comprehensive Database of Escherichia coli Resistance Phenotypes

The microbial ability to resist stressful environmental conditions and chemical inhibitors is of great industrial and medical interest. Much of the data related to mutation-based stress resistance, however, is scattered through the academic literature, making it difficult to apply systematic analyses to this wealth of information. To address this issue, we introduce the Resistome database: a literature-curated collection of Escherichia coli genotypes-phenotypes containing over 5,000 mutants that resist hundreds of compounds and environmental conditions. We use the Resistome to understand our current state of knowledge regarding resistance and to detect potential synergy or antagonism between resistance phenotypes. Our data set represents one of the most comprehensive collections of genomic data related to resistance currently available. Future development will focus on the construction of a combined genomic-transcriptomic-proteomic framework for understanding E. coli's resistance biology. The Resistome can be downloaded at https://bitbucket.org/jdwinkler/resistome_release/overview .

Environmental changes bridge evolutionary valleys

In the basic fitness landscape metaphor for molecular evolution, evolutionary pathways are presumed to follow uphill steps of increasing fitness. How evolution can cross fitness valleys is an open question. One possibility is that environmental changes alter the fitness landscape such that low-fitness sequences reside on a hill in alternate environments. We experimentally test this hypothesis on the antibiotic resistance gene TEM-15 β-lactamase by comparing four evolutionary strategies shaped by environmental changes. The strategy that included initial steps of selecting for low antibiotic resistance (negative selection) produced superior alleles compared with the other three strategies. We comprehensively examined possible evolutionary pathways leading to one such high-fitness allele and found that an initially deleterious mutation is key to the allele's evolutionary history. This mutation is an initial gateway to an otherwise relatively inaccessible area of sequence space and participates in higher-order, positive epistasis with a number of neutral to slightly beneficial mutations. The ability of negative selection and environmental changes to provide access to novel fitness peaks has important implications for natural evolutionary mechanisms and applied directed evolution.

Directed Evolution of RecA Variants with Enhanced Capacity for Conjugational Recombination

The recombination activity of Escherichia coli (E. coli) RecA protein reflects an evolutionary balance between the positive and potentially deleterious effects of recombination. We have perturbed that balance, generating RecA variants exhibiting improved recombination functionality via random mutagenesis followed by directed evolution for enhanced function in conjugation. A recA gene segment encoding a 59 residue segment of the protein (Val79-Ala137), encompassing an extensive subunit-subunit interface region, was subjected to degenerate oligonucleotide-mediated mutagenesis. An iterative selection process generated at least 18 recA gene variants capable of producing a higher yield of transconjugants. Three of the variant proteins, RecA I102L, RecA V79L and RecA E86G/C90G were characterized based on their prominence. Relative to wild type RecA, the selected RecA variants exhibited faster rates of ATP hydrolysis, more rapid displacement of SSB, decreased inhibition by the RecX regulator protein, and in general displayed a greater persistence on DNA. The enhancement in conjugational function comes at the price of a measurable RecA-mediated cellular growth deficiency. Persistent DNA binding represents a barrier to other processes of DNA metabolism in vivo. The growth deficiency is alleviated by expression of the functionally robust RecX protein from Neisseria gonorrhoeae. RecA filaments can be a barrier to processes like replication and transcription. RecA regulation by RecX protein is important in maintaining an optimal balance between recombination and other aspects of DNA metabolism.

The genetic recombination systems of bacteria have not evolved for optimal enzymatic function. As recombination and recombination systems can have deleterious effects, these systems have evolved sufficient function to repair a level of DNA double strand breaks typically encountered during replication and cell division. However, maintenance of genome stability requires a proper balance between all aspects of DNA metabolism. A substantial increase in recombinase function is possible, but it comes with a cellular cost. Here, we use a kind of directed evolution to generate variants of the Escherichia coli RecA protein with an enhanced capacity to promote conjugational recombination. The mutations all occur within a targeted 59 amino acid segment of the protein, encompassing a significant part of the subunit-subunit interface. The RecA variants exhibit a range of altered activities. In general, the mutations appear to increase RecA protein persistence as filaments formed on DNA creating barriers to DNA replication and/or transcription. The barriers can be eliminated via expression of more robust forms of a RecA regulator, the RecX protein. The results elucidate an evolutionary compromise between the beneficial and deleterious effects of recombination.

A comprehensive, high-resolution map of a gene's fitness landscape

Mutations are central to evolution, providing the genetic variation upon which selection acts. A mutation’s effect on the suitability of a gene to perform a particular function (gene fitness) can be positive, negative, or neutral. Knowledge of the distribution of fitness effects (DFE) of mutations is fundamental for understanding evolutionary dynamics, molecular-level genetic variation, complex genetic disease, the accumulation of deleterious mutations, and the molecular clock. We present comprehensive DFEs for point and codon mutants of the Escherichia coli TEM-1 β-lactamase gene and missense mutations in the TEM-1 protein. These DFEs provide insight into the inherent benefits of the genetic code’s architecture, support for the hypothesis that mRNA stability dictates codon usage at the beginning of genes, an extensive framework for understanding protein mutational tolerance, and evidence that mutational effects on protein thermodynamic stability shape the DFE. Contrary to prevailing expectations, we find that deleterious effects of mutation primarily arise from a decrease in specific protein activity and not cellular protein levels.