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.

The causes of evolvability and their evolution.

Evolvability is the ability of a biological system to produce phenotypic variation that is both heritable and adaptive. It has long been the subject of anecdotal observations and theoretical work. In recent years, however, the molecular causes of evolvability have been an increasing focus of experimental work. Here, we review recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates. This research reveals the importance of three major themes: multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography. We also discuss the mounting evidence that evolvability can evolve and the question of whether it evolves adaptively.

Mutation bias shapes the spectrum of adaptive substitutions.

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply ([Formula: see text]) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

Developmental Selection and the Perception of Mutation Bias.

The notion that mutations are random relative to their fitness effects is central to the Neo-Darwinian view of evolution. However, a recent interpretation of the patterns of mutation accumulation in the genome of Arabidopsis thaliana has challenged this notion, arguing for the presence of a targeted DNA repair mechanism that causes a nonrandom association of mutation rates and fitness effects. Specifically, this mechanism was suggested to cause a reduction in the rates of mutations on essential genes, thus lowering the rates of deleterious mutations. Central to this argument were attempts to rule out selection at the population level. Here, we offer an alternative and parsimonious interpretation of the patterns of mutation accumulation previously attributed to mutation bias, showing how they can instead or additionally be caused by developmental selection, that is selection occurring at the cellular level during the development of a multicellular organism. Thus, the depletion of deleterious mutations in A. thaliana may indeed be the result of a selective process, rather than a bias in mutation. More broadly, our work highlights the importance of considering development in the interpretation of population-genetic analyses of multicellular organisms, and it emphasizes that efforts to identify mechanisms involved in mutational biases should explicitly account for developmental selection.

Mutation and Selection Induce Correlations between Selection Coefficients and Mutation Rates.

AbstractThe joint distribution of selection coefficients and mutation rates is a key determinant of the genetic architecture of molecular adaptation. Three different distributions are of immediate interest: (1) the "nominal" distribution of possible changes, prior to mutation or selection; (2) the "de novo" distribution of realized mutations; and (3) the "fixed" distribution of selectively established mutations. Here, we formally characterize the relationships between these joint distributions under the strong-selection/weak-mutation (SSWM) regime. The de novo distribution is enriched relative to the nominal distribution for the highest rate mutations, and the fixed distribution is further enriched for the most highly beneficial mutations. Whereas mutation rates and selection coefficients are often assumed to be uncorrelated, we show that even with no correlation in the nominal distribution, the resulting de novo and fixed distributions can have correlations with any combination of signs. Nonetheless, we suggest that natural systems with a finite number of beneficial mutations will frequently have the kind of nominal distribution that induces negative correlations in the fixed distribution. We apply our mathematical framework, along with population simulations, to explore joint distributions of selection coefficients and mutation rates from deep mutational scanning and cancer informatics. Finally, we consider the evolutionary implications of these joint distributions together with two additional joint distributions relevant to parallelism and the rate of adaptation.

On the incongruence of genotype-phenotype and fitness landscapes.

The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.

Little Evidence the Standard Genetic Code Is Optimized for Resource Conservation.

Selection for resource conservation can shape the coding sequences of organisms living in nutrient-limited environments. Recently, it was proposed that selection for resource conservation, specifically for nitrogen and carbon content, has also shaped the structure of the standard genetic code, such that the missense mutations the code allows tend to cause small increases in the number of nitrogen and carbon atoms in amino acids. Moreover, it was proposed that this optimization is not confounded by known optimizations of the standard genetic code, such as for polar requirement or hydropathy. We challenge these claims. We show the proposed optimization for nitrogen conservation is highly sensitive to choice of null model and the proposed optimization for carbon conservation is confounded by the known conservative nature of the standard genetic code with respect to the molecular volume of amino acids. There is therefore little evidence the standard genetic code is optimized for resource conservation. We discuss our findings in the context of null models of the standard genetic code.

The Adaptive Potential of Nonheritable Somatic Mutations.

AbstractThe adaptive potential of nonheritable somatic mutations has received limited attention in traditional evolutionary theory because heritability is a fundamental pillar of Darwinian evolution. We hypothesized that the ability of a germline genotype to express a novel phenotype via nonheritable somatic mutations can be selectively advantageous and that this advantage will channel evolving populations toward germline genotypes that constitutively express the phenotype. We tested this hypothesis by simulating evolving populations of developing organisms with an impermeable germline-soma separation navigating a minimal fitness landscape. The simulations revealed the conditions under which nonheritable somatic mutations promote adaptation. Specifically, this can occur when the somatic mutation supply is high, when few cells with the advantageous somatic mutation are required to increase organismal fitness, and when the somatic mutation also confers a selective advantage at the cellular level. We therefore provide proof of principle that nonheritable somatic mutations can promote adaptive evolution via a process we call "somatic genotypic exploration." We discuss the biological plausibility of this phenomenon as well as its evolutionary implications.

Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis.

Transition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of the rates and spectra of spontaneous mutations. However, demonstrating the role of transition bias in adaptive evolution remains challenging. In particular, it is unclear whether such biases direct the evolution of bacterial pathogens adapting to treatment. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis (MTB). We found strong evidence for transition bias in two independently curated data sets comprising 152 and 208 antibiotic-resistance mutations. This was true at the level of mutational paths (distinct adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes) and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the 16S ribosomal RNA gene rrs) and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.

Asynchronous Online Instruction Leads to Learning Gaps When Compared to a Flipped Classroom.

With the gradual shift to online education models that has taken place in recent decades, research has sought to understand the nuances of student performance in an online model in comparison to more traditional in-person modalities. However, the effects of instructional modality have been difficult to determine given the many variables that exist in course design between these methods. In this study, we attempt to determine the efficacy of asynchronous online instruction by comparing two nearly equivalent courses. The first course was a flipped classroom, a recent and well-studied hybrid model of instruction. The second was an asynchronous fully online course that contained all the same instructional elements as the in-person course but lacked any student or instructor interaction. Student performance was tracked at both a highly-selective private institution and an open-enrollment public institution. Results show that students' performance drops in an asynchronous online course compared to an equivalent in-person experience. Several potential hypotheses are put forth to explain a change in performance that can potentially shape the design of online instruction.

Enhancers Facilitate the Birth of De Novo Genes and Gene Integration into Regulatory Networks.

Regulatory networks control the spatiotemporal gene expression patterns that give rise to and define the individual cell types of multicellular organisms. In eumetazoa, distal regulatory elements called enhancers play a key role in determining the structure of such networks, particularly the wiring diagram of "who regulates whom." Mutations that affect enhancer activity can therefore rewire regulatory networks, potentially causing adaptive changes in gene expression. Here, we use whole-tissue and single-cell transcriptomic and chromatin accessibility data from mouse to show that enhancers play an additional role in the evolution of regulatory networks: They facilitate network growth by creating transcriptionally active regions of open chromatin that are conducive to de novo gene evolution. Specifically, our comparative transcriptomic analysis with three other mammalian species shows that young, mouse-specific intergenic open reading frames are preferentially located near enhancers, whereas older open reading frames are not. Mouse-specific intergenic open reading frames that are proximal to enhancers are more highly and stably transcribed than those that are not proximal to enhancers or promoters, and they are transcribed in a limited diversity of cellular contexts. Furthermore, we report several instances of mouse-specific intergenic open reading frames proximal to promoters showing evidence of being repurposed enhancers. We also show that open reading frames gradually acquire interactions with enhancers over macroevolutionary timescales, helping integrate genes-those that have arisen de novo or by other means-into existing regulatory networks. Taken together, our results highlight a dual role of enhancers in expanding and rewiring gene regulatory networks.

Cardioneuroablation for cardioinhibitory vasovagal syncope.

BACKGROUND: Cardioneuroablation (CNA) is an emerging technique being used to treat patients with cardioinhibitory vasovagal syncope (VVS). We describe a case of CNA in targeting atrial ganglionated plexi (GP) based upon anatomical landmarks and fractionated electrogram (EGM) localization in a patient with cardioinhibitory syncope. CASE PRESENTATION: A 20-year-old healthy female presented with malignant VVS and symptomatic sinus pauses, with the longest detected at 10 s. She underwent acutely successful CNA with demonstration of vagal response (VR) noted after ablation of left sided GP, and tachycardia noted with right sided GP ablation. All GP sites were defined by anatomical landmarks and EGM analysis. By using the fractionation mapping software of Ensite Precision mapping system with high density mapping, fragmented EGMs were successfully detected in each GP site. One month after vagal denervation, there were no recurrent syncopal episodes or sinus pauses. Longer term follow-up with implantable loop recorder is planned. CONCLUSION: We performed CNA in a patient with VVS by utilizing a novel approach of combined use of high density mapping and fractionation mapping software. With this approach, we were able to detect fractionation in all GP sites and demonstrate acute VR. This workflow may allow for a new, standardized technique suitable for widespread use.

Impact of age on catheter ablation of premature ventricular contractions.

INTRODUCTION: Catheter ablation (CA) of frequent premature ventricular contractions (PVC) is increasingly performed in older patients as the population ages. The aim of this study was to assess the impact of age on procedural characteristics, safety and efficacy on PVC ablations. METHODS: Consecutive patients with symptomatic PVCs undergoing CA between 2015 and 2020 were evaluated. Acute ablation success was defined as the elimination of PVCs at the end of the procedure. Sustained success was defined as an elimination of symptoms, and ≥80% reduction of PVC burden determined by Holter-electrocardiogram during long-term follow. Patients were sub-grouped based on age (<65 vs. ≥65 years). RESULTS: A total of 114 patients were enrolled (median age 64 years, 71% males) and followed up for a median duration of 228 days. Baseline and procedural data were similar in both age groups. A left-sided origin of PVCs was more frequently observed in the elderly patient group compared to younger patients (83% vs. 67%; p = .04). The median procedure time was significantly shorter in elderly patients (160 vs. 193 min; p = .02). The rates of both acute (86% vs. 92%; p = .32) and sustained success (70% vs. 71%; p = .90) were similar between groups. Complications rates (3.7%) did not differ between the two groups. CONCLUSION: In a large series of patients with a variety of underlying arrhythmia substrates, similar rates of acute procedural success, complications, and ventricular arrhythmia-free-survival were observed after CA of PVCs. Older age alone should not be a reason to withhold CA of PVCs.

Mutation bias interacts with composition bias to influence adaptive evolution.

Mutation is a biased stochastic process, with some types of mutations occurring more frequently than others. Previous work has used synthetic genotype-phenotype landscapes to study how such mutation bias affects adaptive evolution. Here, we consider 746 empirical genotype-phenotype landscapes, each of which describes the binding affinity of target DNA sequences to a transcription factor, to study the influence of mutation bias on adaptive evolution of increased binding affinity. By using empirical genotype-phenotype landscapes, we need to make only few assumptions about landscape topography and about the DNA sequences that each landscape contains. The latter is particularly important because the set of sequences that a landscape contains determines the types of mutations that can occur along a mutational path to an adaptive peak. That is, landscapes can exhibit a composition bias-a statistical enrichment of a particular type of mutation relative to a null expectation, throughout an entire landscape or along particular mutational paths-that is independent of any bias in the mutation process. Our results reveal the way in which composition bias interacts with biases in the mutation process under different population genetic conditions, and how such interaction impacts fundamental properties of adaptive evolution, such as its predictability, as well as the evolution of genetic diversity and mutational robustness.

RNA-mediated gene regulation is less evolvable than transcriptional regulation.

Much of gene regulation is carried out by proteins that bind DNA or RNA molecules at specific sequences. One class of such proteins is transcription factors, which bind short DNA sequences to regulate transcription. Another class is RNA binding proteins, which bind short RNA sequences to regulate RNA maturation, transport, and stability. Here, we study the robustness and evolvability of these regulatory mechanisms. To this end, we use experimental binding data from 172 human and fruit fly transcription factors and RNA binding proteins as well as human polymorphism data to study the evolution of binding sites in vivo. We find little difference between the robustness of regulatory protein-RNA interactions and transcription factor-DNA interactions to DNA mutations. In contrast, we find that RNA-mediated regulation is less evolvable than transcriptional regulation, because mutations are less likely to create interactions of an RNA molecule with a new RNA binding protein than they are to create interactions of a gene regulatory region with a new transcription factor. Our observations are consistent with the high level of conservation observed for interactions between RNA binding proteins and their target molecules as well as the evolutionary plasticity of regulatory regions bound by transcription factors. They may help explain why transcriptional regulation is implicated in many more evolutionary adaptations and innovations than RNA-mediated gene regulation.

Electromagnetic interference from left ventricular assist devices in patients with subcutaneous implantable cardioverter-defibrillators.

INTRODUCTION: Interactions of left ventricular assist devices (LVADs) with transvenous implantable cardioverter-defibrillator systems (ICDs) have been widely reported. However, less is known regarding the impact of electromagnetic interference (EMI) from LVADs on subcutaneous ICD function. METHODS AND RESULTS: A comprehensive literature search was performed on PubMed, Cochrane central registry, and Google Scholar using the search terms "subcutaneous implantable cardioverter-defibrillator and left ventricular assist devices," "electromagnetic interference, LVAD, and subcutaneous ICD," "EMI and S-ICD," and "inappropriate shocks, LVAD, and ICD." Demographic and programming data were extracted from the reports and authors as needed. A total of seven cases of EMI in LVAD patients with subcutaneous ICD (S-ICD) devices were found. In addition three previously unreported cases from our center were included. All cases involved either a heartware ventricular assist device or HeartMate III LVAD with a pre-existing S-ICD. In all patients, both the primary and secondary vectors had inappropriate sensing due to EMI. Three patients were reprogramed to the alternate vector with appropriate sensing. The S-ICD was either inactivated or replaced with a transvenous device in six patients. A single patient was left sensing in the alternate vector. There were no reports of inability to interrogate S-ICD systems in patients with LVADs. CONCLUSION: The risk of inappropriate shocks from LVADs should be considered in pre-existing patients with S-ICD, particularly when the heartware ventricular assist device or HeartMate III LVAD device is present. Reprogramming of the sensing vector can occasionally avoid this issue but often the S-ICD needs to be inactivated.

Three-way stopcock suture technique for hemostasis after ablation for atrial fibrillation.

BACKGROUND: Figure-of-eight sutures (F8S) have emerged as an alternative to the standard practice of manual compression to achieve venous hemostasis after catheter ablation for atrial fibrillation (AF). In lieu of a knot to secure the sutures in place, a three-way stopcock can be used, which can be loosened or tightened as needed to achieve hemostasis and is easier to remove. The safety and effectiveness of this technique, when compared to traditional F8S, are unknown. In this case series, we sought to describe this stopcock closure (SC) technique and compare procedural characteristics and outcomes to the traditional F8S. METHODS: Charts of consecutive patients who underwent AF radiofrequency at two centers were reviewed for the type of hemostasis (SC or F8S), demographics, periprocedural anticoagulation, groin complications, and procedural duration. RESULTS: A total of 100 patients were included (50 in the F8S group and 50 in the SC group). The two groups were similar in terms of mean age, gender, weight, renal function, oral anticoagulant use, and procedural heparin dosing. There was one groin bleeding complication in each group. The procedural time was shortened in the SC group (220 ± 8 minutes vs 313 ± 8 minutes), and there was more protamine use (25 vs 3 patients) owing to the differences in preferences among two operators. CONCLUSION: In this proof-of-concept study, a simple stopcock device provided comparable hemostasis to standard F8S after radiofrequency catheter ablation of AF.

Figure-of-eight sutures for hemostasis result in shorter lab recovery time after ablation for atrial fibrillation.

BACKGROUND: Ablation for atrial fibrillation (AF) requires multiple venous sheaths and anticoagulation with heparin, both risk factors for bleeding complications. Manual compression (MC) with heparin reversal is the standard method to achieve venous hemostasis postablation; however, temporary figure-of-eight sutures (F8S) are an alternative. While this technique has been shown to be safe and effective, little is known about its effect on postprocedural recovery time. METHODS: In this retrospective cohort study, consecutive patients who underwent AF radiofrequency ablation over a 23-month period were reviewed for type of hemostasis (manual compression or figure-of-eight suture), demographics, periprocedural anticoagulation, groin complications, and procedural duration. RESULTS: A total of 104 patients were included (42 in the MC group and 62 in the F8S group). The two groups were similar for mean age, gender, weight, oral anticoagulant use, and procedural heparin dosing. Access site complications were 4.76% versus 3.23% (P = 0.68). Time from procedure end to sheath removal was lower in the F8S group (16.2 ± 8.47 vs 4.25 ± 4.14 min, P < 0.0001). Overall time from procedure end to hemostasis was 36.1 ± 10.1 min in the MC group versus 7.9 ± 5.6 in the F8S group (P < 0.0001). Times to extubation and transport out of the lab were both significantly lower in the F8S group (34.1 ± 14.6 vs 13.5 ± 5.4 min, and 44 ± 14.6 vs 21.9 ± 6.7 min, respectively, P < 0.0001). CONCLUSION: Figure-of-eight sutures provided efficient hemostasis following AF ablation, with significantly reduced postprocedure recovery time including time to hemostasis, extubation, and transport out of the lab.

Genonets server-a web server for the construction, analysis and visualization of genotype networks.

A genotype network is a graph in which vertices represent genotypes that have the same phenotype. Edges connect vertices if their corresponding genotypes differ in a single small mutation. Genotype networks are used to study the organization of genotype spaces. They have shed light on the relationship between robustness and evolvability in biological systems as different as RNA macromolecules and transcriptional regulatory circuits. Despite the importance of genotype networks, no tool exists for their automatic construction, analysis and visualization. Here we fill this gap by presenting the Genonets Server, a tool that provides the following features: (i) the construction of genotype networks for categorical and univariate phenotypes from DNA, RNA, amino acid or binary sequences; (ii) analyses of genotype network topology and how it relates to robustness and evolvability, as well as analyses of genotype network topography and how it relates to the navigability of a genotype network via mutation and natural selection; (iii) multiple interactive visualizations that facilitate exploratory research and education. The Genonets Server is freely available at http://ieu-genonets.uzh.ch.

A QS pattern in leads V1 and V2 is associated with septal scarring independent of scar etiology - A cardiac magnetic resonance imaging study.

BACKGROUND: Isolated septal myocardial infarction (MI) is traditionally characterized by the presence of pathological Q waves in leads V1 and V2 on the surface electrocardiogram (ECG). The purpose of this study was to determine the relation between this ECG pattern and septal scar on cardiac magnetic resonance (CMR) imaging. METHODS: We retrospectively reviewed the medical records of 996 consecutive patients who received both ECG and CMR. RESULTS: Nineteen patients had a Q wave in leads V1 and V2. Septal scar was present in all 19 patients. Based on CMR imaging criteria, septal scars were ischemic in 8 patients (42%) and non-ischemic in 11 patients (58%). CONCLUSION: The results suggest that the presence of a QS pattern in leads V1 and V2 on the surface ECG is highly predictive of the presence of a septal myocardial scar, but is not diagnostic for septal MI, even after excluding comorbidities known to produce a pseudo-septal MI pattern.