Evolutionary meandering of intermolecular interactions along the drift barrier

Genetic and selective constraints on the optimization of gene product diversity

RNA and protein expressed from the same gene can have diverse isoforms due to various post-transcriptional and post-translational modifications. For the vast majority of alternative isoforms, It is unknown whether they are adaptive or simply biological noise. As we cannot experimentally probe the function of each isoform, we can ask whether the distribution of isoforms across genes and across species is consistent with expectations from different evolutionary processes. However, there is currently no theoretical framework that can generate such predictions. To address this, we developed a mathematical model where isoform abundances are determined collectively by cis-acting loci, trans-acting factors, gene expression levels, and isoform decay rates to predict isoform abundance distributions across species and genes in the face of mutation, genetic drift, and selection. We found that factors beyond selection, such as effective population size and the number of cis-acting loci, significantly influence evolutionary outcomes. Notably, suboptimal phenotypes are more likely to evolve when the population is small and/or when the number of cis-loci is large. We also explored scenarios where modification processes have both beneficial and detrimental effects, revealing a non-monotonic relationship between effective population size and optimization, demonstrating how opposing selection pressures on cis- and trans-acting loci can constrain the optimization of gene product diversity. As a demonstration of the power of our theory, we compared the expected distribution of A-to-I RNA editing levels in coleoids and found this to be largely consistent with non-adaptive explanations.

The substrate quality of CK2 target sites has a determinant role on their function and evolution

Most biological processes are regulated by signaling modules that bind to short linear motifs. For protein kinases, substrates may have full or only partial matches to the kinase recognition motif, a property known as "substrate quality." However, it is not clear whether differences in substrate quality represent neutral variation or if they have functional consequences. We examine this question for the kinase CK2, which has many fundamental functions. We show that optimal CK2 sites are phosphorylated at maximal stoichiometries and found in many conditions, whereas minimal substrates are more weakly phosphorylated and have regulatory functions. Optimal CK2 sites tend to be more conserved, and substrate quality is often tuned by selection. For intermediate sites, increases or decreases in substrate quality may be deleterious, as we demonstrate for a CK2 substrate at the kinetochore. The results together suggest a strong role for substrate quality in phosphosite function and evolution. A record of this paper's transparent peer review process is included in the supplemental information.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Structural basis for a degenerate tRNA identity code and the evolution of bimodal specificity in human mitochondrial tRNA recognition

Animal mitochondrial gene expression relies on specific interactions between nuclear-encoded aminoacyl-tRNA synthetases and mitochondria-encoded tRNAs. Their evolution involves an antagonistic interplay between strong mutation pressure on mtRNAs and selection pressure to maintain their essential function. To understand the molecular consequences of this interplay, we analyze the human mitochondrial serylation system, in which one synthetase charges two highly divergent mtRNASer isoacceptors. We present the cryo-EM structure of human mSerRS in complex with mtRNASer(UGA), and perform a structural and functional comparison with the mSerRS-mtRNASer(GCU) complex. We find that despite their common function, mtRNASer(UGA) and mtRNASer(GCU) show no constrain to converge on shared structural or sequence identity motifs for recognition by mSerRS. Instead, mSerRS evolved a bimodal readout mechanism, whereby a single protein surface recognizes degenerate identity features specific to each mtRNASer. Our results show how the mutational erosion of mtRNAs drove a remarkable innovation of intermolecular specificity rules, with multiple evolutionary pathways leading to functionally equivalent outcomes.

Transcriptomic, proteomic, and functional consequences of codon usage bias in human cells during heterologous gene expression

Differences in codon frequency between genomes, genes, or positions along a gene, modulate transcription and translation efficiency, leading to phenotypic and functional differences. Here, we present a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells, quantifying the phenotypic consequences of codon usage bias at different molecular and cellular levels, with an emphasis on translation elongation. Six synonymous versions of an antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was analyzed by means of quantitative transcriptome and proteome assessment, as proxies for gene expression; cellular fluorescence, as a proxy for single-cell level expression; and real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness. We show that differences in codon usage bias strongly impact the molecular and cellular phenotype: (i) they result in large differences in mRNA levels and protein levels, leading to differences of over 15 times in translation efficiency; (ii) they introduce unpredicted splicing events; (iii) they lead to reproducible phenotypic heterogeneity; and (iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression. In human cells in culture, codon usage bias modulates gene expression by modifying mRNA availability and suitability for translation, leading to differences in protein levels and eventually eliciting functional phenotypic changes.

Engineering resource allocation in artificially minimized cells: Is genome reduction the best strategy?

The elimination of the expression of cellular functions that are not needed in a certain well-defined artificial environment, such as those used in industrial production facilities, has been the goal of many cellular minimization projects. The generation of a minimal cell with reduced burden and less host-function interactions has been pursued as a tool to improve microbial production strains. In this work, we analysed two cellular complexity reduction strategies: genome and proteome reduction. With the aid of an absolute proteomics data set and a genome-scale model of metabolism and protein expression (ME-model), we quantitatively assessed the difference of reducing genome to the correspondence of reducing proteome. We compare the approaches in terms of energy consumption, defined in ATP equivalents. We aim to show what is the best strategy for improving resource allocation in minimized cells. Our results show that genome reduction by length is not proportional to reducing resource use. When we normalize calculated energy savings, we show that strains with the larger calculated proteome reduction show the largest resource use reduction. Furthermore, we propose that reducing highly expressed proteins should be the target as the translation of a gene uses most of the energy. The strategies proposed here should guide cell design when the aim of a project is to reduce the maximum amount or cellular resources.

Translational regulation by Hfq-Crc assemblies emerges from polymorphic ribonucleoprotein folding

The widely occurring bacterial RNA chaperone Hfq is a key factor in the post-transcriptional control of hundreds of genes in Pseudomonas aeruginosa. How this broadly acting protein can contribute to the regulatory requirements of many different genes remains puzzling. Here, we describe cryo-EM structures of higher order assemblies formed by Hfq and its partner protein Crc on control regions of different P. aeruginosa target mRNAs. Our results show that these assemblies have mRNA-specific quaternary architectures resulting from the combination of multivalent protein-protein interfaces and recognition of patterns in the RNA sequence. The structural polymorphism of these ribonucleoprotein assemblies enables selective translational repression of many different target mRNAs. This system elucidates how highly complex regulatory pathways can evolve with a minimal economy of proteinogenic components in combination with RNA sequence and fold.

Microbial population dynamics decouple growth response from environmental nutrient concentration

How the growth rate of a microbial population responds to the environmental availability of chemical nutrients and other resources is a fundamental question in microbiology. Models of this response, such as the widely used Monod model, are generally characterized by a maximum growth rate and a half-saturation concentration of the resource. What values should we expect for these half-saturation concentrations, and how should they depend on the environmental concentration of the resource? We survey growth response data across a wide range of organisms and resources. We find that the half-saturation concentrations vary across orders of magnitude, even for the same organism and resource. To explain this variation, we develop an evolutionary model to show that demographic fluctuations (genetic drift) can constrain the adaptation of half-saturation concentrations. We find that this effect fundamentally differs depending on the type of population dynamics: Populations undergoing periodic bottlenecks of fixed size will adapt their half-saturation concentrations in proportion to the environmental resource concentrations, but populations undergoing periodic dilutions of fixed size will evolve half-saturation concentrations that are largely decoupled from the environmental concentrations. Our model not only provides testable predictions for laboratory evolution experiments, but it also reveals how an evolved half-saturation concentration may not reflect the organism's environment. In particular, this explains how organisms in resource-rich environments can still evolve fast growth at low resource concentrations. Altogether, our results demonstrate the critical role of population dynamics in shaping fundamental ecological traits.

Supply-driven evolution: Mutation bias and trait-fitness distributions can drive macro-evolutionary dynamics

Many well-documented macro-evolutionary phenomena still challenge current evolutionary theory. Examples include long-term evolutionary trends, major transitions in evolution, conservation of certain biological features such as hox genes, and the episodic creation of new taxa. Here, we present a framework that may explain these phenomena. We do so by introducing a probabilistic relationship between trait value and reproductive fitness. This integration allows mutation bias to become a robust driver of long-term evolutionary trends against environmental bias, in a way that is consistent with all current evolutionary theories. In cases where mutation bias is strong, such as when detrimental mutations are more common than beneficial mutations, a regime called “supply-driven” evolution can arise. This regime can explain the irreversible persistence of higher structural hierarchies, which happens in the major transitions in evolution. We further generalize this result in the long-term dynamics of phenotype spaces. We show how mutations that open new phenotype spaces can become frozen in time. At the same time, new possibilities may be observed as a burst in the creation of new taxa.

Coronary conductance in the normal development of sheep during the perinatal period

Birth is associated with substantial shifts in cardiovascular physiology. Little is known about coronary vascular adaptations during this period. We used fetal and neonatal lambs to measure coronary function at late gestation (92% of term) and shortly after birth (5-6 days postnatal age). In each animal we measured unanesthetized myocardial perfusion and oxygen delivery using a circumflex artery flow probe. We used inflatable occluders and adenosine to determine coronary conductance and flow reserve. In a subset of animals, we used myocardial contrast echocardiography (MCE, anesthetized) to assess its utility as a tool for studying changes in regional myocardial perfusion in normal development. Separate age-matched animals were instrumented with aortic and coronary sinus sampling catheters to determine myocardial oxygen extraction (unanesthetized). With an average of 17 days of developmental time separating our neonatal and fetal cohorts we found that heart-to-body weight ratio was significantly greater in neonates than fetuses. In resting animals, we found significant decreases in weight-normalized perfusion of, and oxygen delivery to, neonatal relative to fetal myocardium. Similar results were seen when measuring baseline MCE-derived perfusion. Pressure-flow relationship studies revealed lower baseline and maximal coronary conductance in neonates than fetuses, with similar coronary flow reserve between groups. There was greater oxygen extraction in neonates than fetuses. Combined analysis of oxygen extraction with coronary flow suggested greater oxygen consumption by the fetal than neonatal myocardium. We conclude that, during the immediate perinatal period, cardiac growth outpaces coronary microvascular growth resulting in lower capacity for microvascular perfusion in the early neonate.

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.

How do mutations change phenotypic traits and organismal fitness? This question is often addressed in the context of a classic metaphor of evolutionary theory—the fitness landscape. A fitness landscape is akin to a physical landscape, in which genotypes define spatial coordinates, and fitness defines the elevation of each coordinate. Evolution then acts like a hill-climbing process, in which populations ascend fitness peaks as a consequence of mutation and selection. It is becoming increasingly common to construct such landscapes using experimental data from high-throughput sequencing technologies and phenotypic assays, in systems such as macromolecules and gene regulatory circuits. Although these landscapes are typically defined by molecular phenotypes, and are therefore more appropriately referred to as genotype-phenotype landscapes, they are often used to study evolutionary dynamics. This requires the assumption that the molecular phenotype is a reasonable proxy for fitness, which need not be the case. For example, selection may favor a low or intermediate phenotypic value, causing incongruence between a fitness landscape and its underlying genotype-phenotype landscape. Here, we study such incongruence using a diversity of theoretical models and experimental data from gene regulatory systems. We regularly find incongruence, in that fitness landscapes tend to comprise more peaks than their underlying genotype-phenotype landscapes. However, using evolutionary simulations, we show that this increased ruggedness need not impede adaptation.

Evolutionary bioenergetics of ciliates

Understanding why various organisms evolve alternative ways of living requires information on both the fitness advantages of phenotypic modifications and the costs of constructing and operating cellular features. Although the former has been the subject of a myriad of ecological studies, almost no attention has been given to how organisms allocate resources to alternative structures and functions. We address these matters by capitalizing on an array of observations on diverse ciliate species and from the emerging field of evolutionary bioenergetics. A relatively robust and general estimator for the total cost of a cell per cell cycle (in units of ATP equivalents) is provided, and this is then used to understand how the magnitudes of various investments scale with cell size. Among other things, we examine the costs associated with the large macronuclear genomes of ciliates, as well as ribosomes, various internal membranes, osmoregulation, cilia, and swimming activities. Although a number of uncertainties remain, the general approach taken may serve as blueprint for expanding this line of work to additional traits and phylogenetic lineages.

Evolution in small steps and giant leaps

The first Editor of Evolution was Ernst Mayr. His foreword to the first issue of Evolution published in 1947 framed evolution as a "problem of interaction" that was just beginning to be studied in this broad context. First, I explore progress and prospects on understanding the subsidiary interactions identified by Mayr, including interactions between parts of organisms, between individuals and populations, between species, and between the organism and its abiotic environment. Mayr's overall "problem of interaction" framework is examined in the context of coevolution within and among levels of biological organization. This leads to a comparison in the relative roles of biotic versus abiotic agents of selection and fluctuating versus directional selection, followed by stabilizing selection in shaping the genomic architecture of adaptation. Oligogenic architectures may be typical for traits shaped more by fluctuating selection and biotic selection. Conversely, polygenic architectures may be typical for traits shaped more by directional followed by stabilizing selection and abiotic selection. The distribution of effect sizes and turnover dynamics of adaptive alleles in these scenarios deserves further study. Second, I review two case studies on the evolution of acquired toxicity in animals, one involving cardiac glycosides obtained from plants and one involving bacterial virulence factors horizontally transferred to animals. The approaches used in these studies and the results gained directly flow from Mayr's vision of an evolutionary biology that revolves around the "problem of interaction."

Evolution of new enzymes by gene duplication and divergence

Thousands of new metabolic and regulatory enzymes have evolved by gene duplication and divergence since the dawn of life. New enzyme activities often originate from promiscuous secondary activities that have become important for fitness due to a change in the environment or a mutation. Mutations that make a promiscuous activity physiologically relevant can occur in the gene encoding the promiscuous enzyme itself, but can also occur elsewhere, resulting in increased expression of the enzyme or decreased competition between the native and novel substrates for the active site. If a newly useful activity is inefficient, gene duplication/amplification will set the stage for divergence of a new enzyme. Even a few mutations can increase the efficiency of a new activity by orders of magnitude. As efficiency increases, amplified gene arrays will shrink to provide two alleles, one encoding the original enzyme and one encoding the new enzyme. Ultimately, genomic rearrangements eliminate co-amplified genes and move newly evolved paralogs to a distant region of the genome.

Positioning Bacillus subtilis as terpenoid cell factory

Increasing demands for bioactive compounds have motivated researchers to employ micro‐organisms to produce complex natural products. Currently, Bacillus subtilis has been attracting lots of attention to be developed into terpenoids cell factories due to its generally recognized safe status and high isoprene precursor biosynthesis capacity by endogenous methylerythritol phosphate (MEP) pathway. In this review, we describe the up‐to‐date knowledge of each enzyme in MEP pathway and the subsequent steps of isomerization and condensation of C5 isoprene precursors. In addition, several representative terpene synthases expressed in B. subtilis and the engineering steps to improve corresponding terpenoids production are systematically discussed. Furthermore, the current available genetic tools are mentioned as along with promising strategies to improve terpenoids in B. subtilis, hoping to inspire future directions in metabolic engineering of B. subtilis for further terpenoid cell factory development.

Directional auxin fluxes in plants by intramolecular domain-domain coevolution of PIN auxin transporters

Morphogenesis and adaptive tropic growth in plants depend on gradients of the phytohormone auxin, mediated by the membrane-based PIN-FORMED (PIN) auxin transporters. PINs localize to a particular side of the plasma membrane (PM) or to the endoplasmic reticulum (ER) to directionally transport auxin and maintain intercellular and intracellular auxin homeostasis, respectively. However, the molecular cues that confer their diverse cellular localizations remain largely unknown. In this study, we systematically swapped the domains between ER- and PM-localized PIN proteins, as well as between apical and basal PM-localized PINs from Arabidopsis thaliana, to shed light on why PIN family members with similar topological structures reside at different membrane compartments within cells. Our results show that not only do the N- and C-terminal transmembrane domains (TMDs) and central hydrophilic loop contribute to their differential subcellular localizations and cellular polarity, but that the pairwise-matched N- and C-terminal TMDs resulting from intramolecular domain-domain coevolution are also crucial for their divergent patterns of localization. These findings illustrate the complexity of the evolutionary path of PIN proteins in acquiring their plethora of developmental functions and adaptive growth in plants.

A Bacterial Tower of Babel: Quorum-Sensing Signaling Diversity and Its Evolution

Quorum sensing is a process in which bacteria secrete and sense a diffusible molecule, thereby enabling bacterial groups to coordinate their behavior in a density-dependent manner. Quorum sensing has evolved multiple times independently, utilizing different molecular pathways and signaling molecules. A common theme among many quorum-sensing families is their wide range of signaling diversity-different variants within a family code for different signal molecules with a cognate receptor specific to each variant. This pattern of vast allelic polymorphism raises several questions-How do different signaling variants interact with one another? How is this diversity maintained? And how did it come to exist in the first place? Here we argue that social interactions between signaling variants can explain the emergence and persistence of signaling diversity throughout evolution. Finally, we extend the discussion to include cases where multiple diverse systems work in concert in a single bacterium.

The evolutionary scaling of cellular traits imposed by the drift barrier

Owing to internal homeostatic mechanisms, cellular traits may experience long periods of stable selective pressures, during which the stochastic forces of drift and mutation conspire to generate variation. However, even in the face of invariant selection, the drift barrier defined by the genetic effective population size, which is negatively associated with organism size, can have a substantial influence on the location and dispersion of the long-term steady-state distribution of mean phenotypes. In addition, for multilocus traits, the multiplicity of alternative, functionally equivalent states can draw mean phenotypes away from selective optima, even in the absence of mutation bias. Using a framework for traits with an additive genetic basis, it is shown that 1) optimal phenotypic states may be only rarely achieved; 2) gradients of mean phenotypes with respect to organism size (i.e., allometric relationships) are likely to be molded by differences in the power of random genetic drift across the tree of life; and 3) for any particular set of population-genetic conditions, significant variation in mean phenotypes may exist among lineages exposed to identical selection pressures. These results provide a potentially useful framework for understanding numerous aspects of cellular diversification and illustrate the risks of interpreting such variation in a purely adaptive framework.

Dormancy cycling: translation-related transcripts are the main difference between dormant and non-dormant seeds in the field

Primary seed dormancy is a mechanism that orchestrates the timing of seed germination in order to prevent out-of-season germination. Secondary dormancy can be induced in imbibed seeds when they encounter prolonged unfavourable conditions. Secondary dormancy is not induced during dry storage, and therefore the mechanisms underlying this process have remained largely unexplored. Here, a 2-year seed burial experiment in which dormancy cycling was studied at the physiological and transcriptional level is presented. For these analyses six different Arabidopsis thaliana genotypes were used: Landsberg erecta (Ler) and the dormancy associated DELAY OF GERMINATION (DOG) near-isogenic lines 1, 2, 3, 6 and 22 (NILDOG1, 2, 3, 6 and 22). The germination potential of seeds exhumed from the field showed that these seeds go through dormancy cycling and that the dynamics of this cycling is genotype dependent. RNA-seq analysis revealed large transcriptional changes during dormancy cycling, especially at the time points preceding shifts in dormancy status. Dormancy cycling is driven by soil temperature and the endosperm is important in the perception of the environment. Genes that are upregulated in the low- to non-dormant stages are enriched for genes involved in translation, indicating that the non-dormant seeds are prepared for rapid seed germination.

Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression

It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

Developmental Systems Drift and the Drivers of Sex Chromosome Evolution

Phenotypic invariance—the outcome of purifying selection—is a hallmark of biological importance. However, invariant phenotypes might be controlled by diverged genetic systems in different species. Here, we explore how an important and invariant phenotype—the development of sexually differentiated individuals—is controlled in over two dozen species in the frog family Pipidae. We uncovered evidence in different species for 1) an ancestral W chromosome that is not found in many females and is found in some males, 2) independent losses and 3) autosomal segregation of this W chromosome, 4) changes in male versus female heterogamy, and 5) substantial variation among species in recombination suppression on sex chromosomes. We further provide evidence of, and evolutionary context for, the origins of at least seven distinct systems for regulating sex determination among three closely related genera. These systems are distinct in their genomic locations, evolutionary origins, and/or male versus female heterogamy. Our findings demonstrate that the developmental control of sexual differentiation changed via loss, sidelining, and empowerment of a mechanistically influential gene, and offer insights into novel factors that impinge on the diverse evolutionary fates of sex chromosomes.

Cell Fuelling and Metabolic Energy Conservation in Synthetic Cells

We are aiming for a blue print for synthesizing (moderately complex) subcellular systems from molecular components and ultimately for constructing life. However, without comprehensive instructions and design principles, we rely on simple reaction routes to operate the essential functions of life. The first forms of synthetic life will not make every building block for polymers de novo according to complex pathways, rather they will be fed with amino acids, fatty acids and nucleotides. Controlled energy supply is crucial for any synthetic cell, no matter how complex. Herein, we describe the simplest pathways for the efficient generation of ATP and electrochemical ion gradients. We have estimated the demand for ATP by polymer synthesis and maintenance processes in small cell-like systems, and we describe circuits to control the need for ATP. We also present fluorescence-based sensors for pH, ionic strength, excluded volume, ATP/ADP, and viscosity, which allow the major physicochemical conditions inside cells to be monitored and tuned.

Weak Chemical Interactions That Drive Protein Evolution: Crowding, Sticking, and Quinary Structure in Folding and Function

In recent years, better instrumentation and greater computing power have enabled the imaging of elusive biomolecule dynamics in cells, driving many advances in understanding the chemical organization of biological systems. The focus of this Review is on interactions in the cell that affect both biomolecular stability and function and modulate them. The same protein or nucleic acid can behave differently depending on the time in the cell cycle, the location in a specific compartment, or the stresses acting on the cell. We describe in detail the crowding, sticking, and quinary structure in the cell and the current methods to quantify them both in vitro and in vivo. Finally, we discuss protein evolution in the cell in light of current biophysical evidence. We describe the factors that drive protein evolution and shape protein interaction networks. These interactions can significantly affect the free energy, ΔG, of marginally stable and low-population proteins and, due to epistasis, direct the evolutionary pathways in an organism. We finally conclude by providing an outlook on experiments to come and the possibility of collaborative evolutionary biology and biophysical efforts.

Biophysics and population size constrains speciation in an evolutionary model of developmental system drift

Developmental system drift is a likely mechanism for the origin of hybrid incompatibilities between closely related species. We examine here the detailed mechanistic basis of hybrid incompatibilities between two allopatric lineages, for a genotype-phenotype map of developmental system drift under stabilising selection, where an organismal phenotype is conserved, but the underlying molecular phenotypes and genotype can drift. This leads to number of emergent phenomenon not obtainable by modelling genotype or phenotype alone. Our results show that: 1) speciation is more rapid at smaller population sizes with a characteristic, Orr-like, power law, but at large population sizes slow, characterised by a sub-diffusive growth law; 2) the molecular phenotypes under weakest selection contribute to the earliest incompatibilities; and 3) pair-wise incompatibilities dominate over higher order, contrary to previous predictions that the latter should dominate. The population size effect we find is consistent with previous results on allopatric divergence of transcription factor-DNA binding, where smaller populations have common ancestors with a larger drift load because genetic drift favours phenotypes which have a larger number of genotypes (higher sequence entropy) over more fit phenotypes which have far fewer genotypes; this means less substitutions are required in either lineage before incompatibilities arise. Overall, our results indicate that biophysics and population size provide a much stronger constraint to speciation than suggested by previous models, and point to a general mechanistic principle of how incompatibilities arise the under stabilising selection for an organismal phenotype.

The process of speciation is of fundamental importance to the field of evolution as it is intimately connected to understanding the immense bio-diversity of life. There is still relatively little understanding of the underlying genetic mechanisms that give rise to hybrid incompatibilities with results suggesting that divergence in transcription factor DNA binding and gene expression play an important role. A key finding from the field of evo-devo is that organismal phenotypes show developmental system drift, where species maintain the same phenotype, but diverge in developmental pathways; this is an important potential source of hybrid incompatibilities. Here, we explore a theoretical framework to understand how incompatibilities arise due to developmental system drift, using a tractable biophysically inspired genotype-phenotype for spatial gene expression. Modelling the evolution of phenotypes in this way has the key advantage that it mirrors how selection works in nature, i.e. that selection acts on phenotypes, but variation (mutation) arise at the level of genotypes. This results, as we demonstrate, in a number of non-trivial and testable predictions concerning speciation due to developmental system drift, which would not be obtainable by modelling evolution of genotypes or phenotypes alone.

Survival of the simplest in microbial evolution

The evolution of microbial and viral organisms often generates clonal interference, a mode of competition between genetic clades within a population. Here we show how interference impacts systems biology by constraining genetic and phenotypic complexity. Our analysis uses biophysically grounded evolutionary models for molecular phenotypes, such as fold stability and enzymatic activity of genes. We find a generic mode of phenotypic interference that couples the function of individual genes and the population’s global evolutionary dynamics. Biological implications of phenotypic interference include rapid collateral system degradation in adaptation experiments and long-term selection against genome complexity: each additional gene carries a cost proportional to the total number of genes. Recombination above a threshold rate can eliminate this cost, which establishes a universal, biophysically grounded scenario for the evolution of sex. In a broader context, our analysis suggests that the systems biology of microbes is strongly intertwined with their mode of evolution.

In asexual populations selection at different genomic loci can interfere with each other. Here, using a biophysical model of molecular evolution the authors show that interference results in long-term degradation of molecular function, an effect that strongly depends on genome size.

Closely related viruses of the marine picoeukaryotic alga Ostreococcus lucimarinus exhibit different ecological strategies

In marine ecosystems, viruses are major disrupters of the direct flow of carbon and nutrients to higher trophic levels. Although the genetic diversity of several eukaryotic phytoplankton virus groups has been characterized, their infection dynamics are less understood, such that the physiological and ecological implications of their diversity remain unclear. We compared genomes and infection phenotypes of the two most closely related cultured phycodnaviruses infecting the widespread picoprasinophyte Ostreococcus lucimarinus under standard- (1.3 divisions per day) and limited-light (0.41 divisions per day) nutrient replete conditions. OlV7 infection caused early arrest of the host cell cycle, coinciding with a significantly higher proportion of infected cells than OlV1-amended treatments, regardless of host growth rate. OlV7 treatments showed a near-50-fold increase of progeny virions at the higher host growth rate, contrasting with OlV1's 16-fold increase. However, production of OlV7 virions was more sensitive than OlV1 production to reduced host growth rate, suggesting fitness trade-offs between infection efficiency and resilience to host physiology. Moreover, although organic matter released from OlV1- and OlV7-infected hosts had broadly similar chemical composition, some distinct molecular signatures were observed. Collectively, these results suggest that current views on viral relatedness through marker and core gene analyses underplay operational divergence and consequences for host ecology.

Defining lower limits of biodegradation: atrazine degradation regulated by mass transfer and maintenance demand in Arthrobacter aurescens TC1

Exploring adaptive strategies by which microorganisms function and survive in low-energy natural environments remains a grand goal of microbiology, and may help address a prime challenge of the 21st century: degradation of man-made chemicals at low concentrations (“micropollutants”). Here we explore physiological adaptation and maintenance energy requirements of a herbicide (atrazine)-degrading microorganism (Arthrobacter aurescens TC1) while concomitantly observing mass transfer limitations directly by compound-specific isotope fractionation analysis. Chemostat-based growth triggered the onset of mass transfer limitation at residual concentrations of 30 μg L⁻¹ of atrazine with a bacterial population doubling time (t_d) of 14 days, whereas exacerbated energy limitation was induced by retentostat-based near-zero growth (t_d = 265 days) at 12 ± 3 μg L⁻¹ residual concentration. Retentostat cultivation resulted in (i) complete mass transfer limitation evidenced by the disappearance of isotope fractionation (ε¹³C = −0.45‰ ± 0.36‰) and (ii) a twofold decrease in maintenance energy requirement compared with chemostat cultivation. Proteomics revealed that retentostat and chemostat cultivation under mass transfer limitation share low protein turnover and expression of stress-related proteins. Mass transfer limitation effectuated slow-down of metabolism in retentostats and a transition from growth phase to maintenance phase indicating a limit of ≈10 μg L⁻¹ for long-term atrazine degradation. Further studies on other ecosystem-relevant microorganisms will substantiate the general applicability of our finding that mass transfer limitation serves as a trigger for physiological adaptation, which subsequently defines a lower limit of biodegradation.

Match fitness landscapes for macromolecular interaction networks: Selection for translational accuracy and rate can displace tRNA-binding interfaces of non-cognate aminoacyl-tRNA synthetases

Advances in structural biology of aminoacyl-tRNA synthetases (aaRSs) have revealed incredible diversity in how aaRSs bind their tRNA substrates. The causes of this diversity remain mysterious. We developed a new class of highly rugged fitness landscape models called match landscapes, through which genes encode the assortative interactions of their gene products through the complementarity and identifiability of their structural features. We used results from coding theory to prove bounds and equalities on fitness in match landscapes assuming additive interaction energies, macroscopic aminoacylation kinetics including proofreading, site-specific modifiers of interaction, and selection for translational accuracy in multiple, perfectly encoded site-types. Using genotypes based on extended Hamming codes we show that over a wide array of interface sizes and numbers of encoded cognate pairs, selection for translational accuracy alone is insufficient to displace the tRNA-binding interfaces of aaRSs. Yet, under combined selection for translational accuracy and rate, site-specific modifiers are selected to adaptively displace the tRNA-binding interfaces of non-cognate aaRS-tRNA pairs. We describe a remarkable correspondence between the lengths of perfect RNA (quaternary) codes and the modal sizes of small non-coding RNA families.

Transcriptional noise and exaptation as sources for bacterial sRNAs

Understanding how new genes originate and integrate into cellular networks is key to understanding evolution. Bacteria present unique opportunities for both the natural history and experimental study of gene origins, due to their large effective population sizes, rapid generation times, and ease of genetic manipulation. Bacterial small non-coding RNAs (sRNAs), in particular, many of which operate through a simple antisense regulatory logic, may serve as tractable models for exploring processes of gene origin and adaptation. Understanding how and on what timescales these regulatory molecules arise has important implications for understanding the evolution of bacterial regulatory networks, in particular, for the design of comparative studies of sRNA function. Here, we introduce relevant concepts from evolutionary biology and review recent work that has begun to shed light on the timescales and processes through which non-functional transcriptional noise is co-opted to provide regulatory functions. We explore possible scenarios for sRNA origin, focusing on the co-option, or exaptation, of existing genomic structures which may provide protected spaces for sRNA evolution.

The novel EHEC gene asa overlaps the TEGT transporter gene in antisense and is regulated by NaCl and growth phase

Only a few overlapping gene pairs are known in the best-analyzed bacterial model organism Escherichia coli. Automatic annotation programs usually annotate only one out of six reading frames at a locus, allowing only small overlaps between protein-coding sequences. However, both RNAseq and RIBOseq show signals corresponding to non-trivially overlapping reading frames in antisense to annotated genes, which may constitute protein-coding genes. The transcription and translation of the novel 264 nt gene asa, which overlaps in antisense to a putative TEGT (Testis-Enhanced Gene Transfer) transporter gene is detected in pathogenic E. coli, but not in two apathogenic E. coli strains. The gene in E. coli O157:H7 (EHEC) was further analyzed. An overexpression phenotype was identified in two stress conditions, i.e. excess in salt or arginine. For this, EHEC overexpressing asa was grown competitively against EHEC with a translationally arrested asa mutant gene. RT-qPCR revealed conditional expression dependent on growth phase, sodium chloride, and arginine. Two potential promoters were computationally identified and experimentally verified by reporter gene expression and determination of the transcription start site. The protein Asa was verified by Western blot. Close homologues of asa have not been found in protein databases, but bioinformatic analyses showed that it may be membrane associated, having a largely disordered structure.

Stochastic protein multimerization, activity, and fitness

Many proteins assemble into homomultimeric structures, with a number of subunits that can vary substantially among phylogenetic lineages. As protein-protein interactions require productive encounters among subunits, such variation might partially be explained by variation in cellular protein abundance. Protein abundance in turn depends on the intrinsic rates of production and decay of mRNA and protein molecules, as well as rates of cell growth and division. Using a stochastic framework for prediction of the multimeric state of a protein as a function of these processes and the free energy associated with interface-interface binding, we demonstrate agreement with a wide class of proteins using E. coli proteome data. As such, this platform, which links protein quaternary structure with biochemical rates governing gene expression, protein association and dissociation, and cell growth and division, can be extended to evolutionary models for the emergence and diversification of multimers. While it is tempting to think of multimerization as adaptive, the diversity of multimeric states raises the question of its functional role and impact on fitness. As a force driving selection, we consider the possible increase in enzymatic activity of proteins arising strictly as a consequence of interface-interface binding-namely, enhanced stability to degradation, substrate binding affinity, or catalytic rate of multimers with respect to monomers without invoking further conformational changes, as in allostery. For fixed cost of protein production, we find a benefit conferred by multimers that is dependent on context and can therefore become different in diverging lineages.

Response to Martin and colleagues: mitochondria do not boost the bioenergetic capacity of eukaryotic cells

A recent paper by (Gerlitz et al., Biol Direct 13:21, 2018) questions the validity of the data underlying prior analyses on the bioenergetics capacities of cells, and continues to promote the idea that the mitochondrion endowed eukaryotic cells with energetic superiority over prokaryotes. The former point has been addressed previously, with no resultant changes in the conclusions, and the latter point remains inconsistent with multiple lines of empirical data.

Elusive data underlying debate at the prokaryote-eukaryote divide

Background

The origin of eukaryotic cells was an important transition in evolution. The factors underlying the origin and evolutionary success of the eukaryote lineage are still discussed. One camp argues that mitochondria were essential for eukaryote origin because of the unique configuration of internalized bioenergetic membranes that they conferred to the common ancestor of all known eukaryotic lineages. A recent paper by Lynch and Marinov concluded that mitochondria were energetically irrelevant to eukaryote origin, a conclusion based on analyses of previously published numbers of various molecules and ribosomes per cell and cell volumes as a presumed proxy for the role of mitochondria in evolution. Their numbers were purportedly extracted from the literature.

Results

We have examined the numbers upon which the recent study was based. We report that for a sample of 80 numbers that were purportedly extracted from the literature and that underlie key inferences of the recent study, more than 50% of the values do not exist in the cited papers to which the numbers are attributed. The published result cannot be independently reproduced. Other numbers that the recent study reports differ inexplicably from those in the literature to which they are ascribed. We list the discrepancies between the recently published numbers and the purported literature sources of those numbers in a head to head manner so that the discrepancies are readily evident, although the source of error underlying the discrepancies remains obscure.

Conclusion

The data purportedly supporting the view that mitochondria had no impact upon eukaryotic evolution data exhibits notable irregularities. The paper in question evokes the impression that the published numbers are of up to seven significant digit accuracy, when in fact more than half the numbers are nowhere to be found in the literature to which they are attributed. Though the reasons for the discrepancies are unknown, it is important to air these issues, lest the prominent paper in question become a point source of a snowballing error through the literature or become interpreted as a form of evidence that mitochondria were irrelevant to eukaryote evolution.

Reviewers

This article was reviewed by Eric Bapteste, Jianzhi Zhang and Martin Lercher.

Synchronous birth is a dominant pattern in receptor-ligand evolution

Background

Interactions between proteins are key components in the chemical and physical processes of living organisms. Among these interactions, membrane receptors and their ligands are particularly important because they are at the interface between extracellular and intracellular environments. Many studies have investigated how binding partners have co-evolved in genomes during the evolution. However, little is known about the establishment of the interaction on a phylogenetic scale.

In this study, we systematically studied the time of birth of genes encoding human membrane receptors and their ligands in the animal tree of life. We examined a total of 553 pairs of ligands/receptors, representing non-redundant interactions.

Results

We found that 41% of the receptors and their respective first ligands appeared in the same branch, representing 2.5-fold more than expected by chance, thus suggesting an evolutionary dynamic of interdependence and conservation between these partners. In contrast, 21% of the receptors appeared after their ligand, i.e. three-fold less often than expected by chance. Most surprisingly, 38% of the receptors appeared before their first ligand, as much as expected by chance.

Conclusions

According to these results, we propose that a selective pressure is exerted on ligands and receptors once they appear, that would remove molecules whose partner does not appear quickly.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4977-2) contains supplementary material, which is available to authorized users.

Integrative analysis of fitness and metabolic effects of plasmids in Pseudomonas aeruginosa PAO1

Horizontal gene transfer (HGT) mediated by the spread of plasmids fuels evolution in prokaryotes. Although plasmids provide bacteria with new adaptive genes, they also produce physiological alterations that often translate into a reduction in bacterial fitness. The fitness costs associated with plasmids represent an important limit to plasmid maintenance in bacterial communities, but their molecular origins remain largely unknown. In this work, we combine phenomics, transcriptomics and metabolomics to study the fitness effects produced by a collection of diverse plasmids in the opportunistic pathogen Pseudomonas aeruginosa PAO1. Using this approach, we scan the physiological changes imposed by plasmids and test the generality of some main mechanisms that have been proposed to explain the cost of HGT, including increased biosynthetic burden, reduced translational efficiency, and impaired chromosomal replication. Our results suggest that the fitness effects of plasmids have a complex origin, since none of these mechanisms could individually provide a general explanation for the cost of plasmid carriage. Interestingly, our results also showed that plasmids alter the expression of a common set of metabolic genes in PAO1, and produce convergent changes in host cell metabolism. These surprising results suggest that there is a common metabolic response to plasmids in P. aeruginosa PAO1.

Phylogenetic divergence of cell biological features

Most cellular features have a range of states, but understanding the mechanisms responsible for interspecific divergence is a challenge for evolutionary cell biology. Models are developed for the distribution of mean phenotypes likely to evolve under the joint forces of mutation and genetic drift in the face of constant selection pressures. Mean phenotypes will deviate from optimal states to a degree depending on the effective population size, potentially leading to substantial divergence in the absence of diversifying selection. The steady-state distribution for the mean can even be bimodal, with one domain being largely driven by selection and the other by mutation pressure, leading to the illusion of phenotypic shifts being induced by movement among alternative adaptive domains. These results raise questions as to whether lineage-specific selective pressures are necessary to account for interspecific divergence, providing a possible platform for the establishment of null models for the evolution of cell-biological traits.

Burden-driven feedback control of gene expression

Cells use feedback regulation to ensure robust growth despite fluctuating demands for resources and differing environmental conditions. However, the expression of foreign proteins from engineered constructs is an unnatural burden that cells are not adapted for. Here we combined RNA-seq with an in vivo assay to identify the major transcriptional changes that occur in Escherichia coli when inducible synthetic constructs are expressed. We observed that native promoters related to the heat-shock response activated expression rapidly in response to synthetic expression, regardless of the construct. Using these promoters, we built a dCas9-based feedback-regulation system that automatically adjusts the expression of a synthetic construct in response to burden. Cells equipped with this general-use controller maintained their capacity for native gene expression to ensure robust growth and thus outperformed unregulated cells in terms of protein yield in batch production. This engineered feedback is to our knowledge the first example of a universal, burden-based biomolecular control system and is modular, tunable and portable.

ChIP-ping the branches of the tree: functional genomics and the evolution of eukaryotic gene regulation

Advances in the methods for detecting protein-DNA interactions have played a key role in determining the directions of research into the mechanisms of transcriptional regulation. The most recent major technological transformation happened a decade ago, with the move from using tiling arrays [chromatin immunoprecipitation (ChIP)-on-Chip] to high-throughput sequencing (ChIP-seq) as a readout for ChIP assays. In addition to the numerous other ways in which it is superior to arrays, by eliminating the need to design and manufacture them, sequencing also opened the door to carrying out comparative analyses of genome-wide transcription factor occupancy across species and studying chromatin biology in previously less accessible model and nonmodel organisms, thus allowing us to understand the evolution and diversity of regulatory mechanisms in unprecedented detail. Here, we review the biological insights obtained from such studies in recent years and discuss anticipated future developments in the field.

Hill kinetics as a noise filter: the role of transcription factor autoregulation in gene cascades

An intuition based on deterministic models of chemical kinetics is that population heterogeneity of transcription factor levels in cells is transmitted unchanged downstream to the target genes. We use a stochastic model of a two-gene cascade with a self-regulating upstream gene to show that, counter to the intuition, there is no simple mapping (bimodal to bimodal, unimodal to unimodal) between the shapes of the distributions of transcription factor numbers and target protein numbers in cells. Due to the presence of the two regulations, the system contains two nonlinear transfer functions, defined by the Hill kinetics of transcription factor binding. The transfer function of the regulator can "interfere" with the transfer function of the target, converting the bimodal input into a unimodal output or vice versa. We show that this effect can be predicted by a geometric construction. As an example application of the method, we present a case study of a system of several downstream genes of different sensitivities, controlled by a common transcription factor which also regulates its own transcription. We show that a single regulator can induce qualitatively different patterns (binary or graded) of responses to a signal in different downstream genes, depending on whether the sensitivity regions of the transfer functions of the upstream and downstream genes overlap or not. Alternatively, the same model can be interpreted as describing a single downstream gene that has different sensitivities in different cell lines due to mutations. Our model shows, therefore, a possible kinetic mechanism by which different genes can interpret the same biological signal in a different manner.

Engineering bacteria for diagnostic and therapeutic applications

Our ability to generate bacterial strains with unique and increasingly complex functions has rapidly expanded in recent times. The capacity for DNA synthesis is increasing and costing less; new tools are being developed for fast, large-scale genetic manipulation; and more tested genetic parts are available for use, as is the knowledge of how to use them effectively. These advances promise to unlock an exciting array of 'smart' bacteria for clinical use but will also challenge scientists to better optimize preclinical testing regimes for early identification and validation of promising strains and strategies. Here, we review recent advances in the development and testing of engineered bacterial diagnostics and therapeutics. We highlight new technologies that will assist the development of more complex, robust and reliable engineered bacteria for future clinical applications, and we discuss approaches to more efficiently evaluate engineered strains throughout their preclinical development.

Equal fitness paradigm explained by a trade-off between generation time and energy production rate

Most plant, animal and microbial species of widely varying body size and lifestyle are nearly equally fit as evidenced by their coexistence and persistence through millions of years. All organisms compete for a limited supply of organic chemical energy, derived mostly from photosynthesis, to invest in the two components of fitness: survival and production. All organisms are mortal because molecular and cellular damage accumulates over the lifetime; life persists only because parents produce offspring. We call this the equal fitness paradigm. The equal fitness paradigm occurs because: (1) there is a trade-off between generation time and productive power, which have equal-but-opposite scalings with body size and temperature; smaller and warmer organisms have shorter lifespans but produce biomass at higher rates than larger and colder organisms; (2) the energy content of biomass is essentially constant, ~22.4 kJ g^-1 dry body weight; and (3) the fraction of biomass production incorporated into surviving offspring is also roughly constant, ~10-50%. As organisms transmit approximately the same quantity of energy per gram to offspring in the next generation, no species has an inherent lasting advantage in the struggle for existence. The equal fitness paradigm emphasizes the central importance of energy, biological scaling relations and power-time trade-offs in life history, ecology and evolution.

Evolution with a seed bank: The population genetic consequences of microbial dormancy

Dormancy is a bet‐hedging strategy that allows organisms to persist through conditions that are suboptimal for growth and reproduction by entering a reversible state of reduced metabolic activity. Dormancy allows a population to maintain a reservoir of genetic and phenotypic diversity (i.e., a seed bank) that can contribute to the long‐term survival of a population. This strategy can be potentially adaptive and has long been of interest to ecologists and evolutionary biologists. However, comparatively little is known about how dormancy influences the fundamental evolutionary forces of genetic drift, mutation, selection, recombination, and gene flow. Here, we investigate how seed banks affect the processes underpinning evolution by reviewing existing theory, implementing novel simulations, and determining how and when dormancy can influence evolution as a population genetic process. We extend our analysis to examine how seed banks can alter macroevolutionary processes, including rates of speciation and extinction. Through the lens of population genetic theory, we can understand the extent that seed banks influence the evolutionary dynamics of microorganisms as well as other taxa.

Characterization of dFOXO binding sites upstream of the Insulin Receptor P2 promoter across the Drosophila phylogeny

The insulin/TOR signal transduction pathway plays a critical role in determining such important traits as body and organ size, metabolic homeostasis and life span. Although this pathway is highly conserved across the animal kingdom, the affected traits can exhibit important differences even between closely related species. Evolutionary studies of regulatory regions require the reliable identification of transcription factor binding sites. Here we have focused on the Insulin Receptor (InR) expression from its P2 promoter in the Drosophila genus, which in D. melanogaster is up-regulated by hypophosphorylated Drosophila FOXO (dFOXO). We have finely characterized this transcription factor binding sites in vitro along the 1.3 kb region upstream of the InR P2 promoter in five Drosophila species. Moreover, we have tested the effect of mutations in the characterized dFOXO sites of D. melanogaster in transgenic flies. The number of experimentally established binding sites varies across the 1.3 kb region of any particular species, and their distribution also differs among species. In D. melanogaster, InR expression from P2 is differentially affected by dFOXO binding sites at the proximal and distal halves of the species 1.3 kb fragment. The observed uneven distribution of binding sites across this fragment might underlie their differential contribution to regulate InR transcription.

Regulatory network structure determines patterns of intermolecular epistasis

Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution.

Musings on mechanism: quest for a quark theory of proteins?

The give and take between biology and physics is an important part of the history of modern science, with this partnership perhaps now more intimate than ever. In this essay, I explore the ways in which these different fields can strengthen each other through their distinct outlooks on some of the most important questions being asked about the living world. In particular, I highlight three areas where the perspective from physics might lead to deeper insights into the workings of cells. First, I consider what it means for two ostensibly unrelated problems to be the same, and how such sameness can provide unexpected insights into apparently unrelated phenomena. Second, I consider different conceptions of what constitutes a mechanistic understanding of a given phenomenon with an emphasis on nonmolecular notions of mechanism. The third idea is the importance of "toy problems" as a way of providing foundational insights into the real problems. Though my focus here is primarily on ways in which physics approaches might prove interesting in biology, I close with an example of how biology might substantially alter physics by providing a forum and the tools to uncover a fundamental understanding of nonequilibrium phenomena.-Phillips, R. Musings on mechanism: quest for a quark theory of proteins?

Alternative evolutionary histories in the sequence space of an ancient protein

To understand why molecular evolution turned out as it did, we must characterize not only the path that evolution followed across the space of possible molecular sequences but also the many alternative trajectories that could have been taken but were not. A large-scale comparison of real and possible histories would establish whether the outcome of evolution represents an optimal state driven by natural selection or the contingent product of historical chance events; it would also reveal how the underlying distribution of functions across sequence space shaped historical evolution. Here we combine ancestral protein reconstruction with deep mutational scanning to characterize alternative histories in the sequence space around an ancient transcription factor, which evolved a novel biological function through well-characterized mechanisms. We find hundreds of alternative protein sequences that use diverse biochemical mechanisms to perform the derived function at least as well as the historical outcome. These alternatives all require prior permissive substitutions that do not enhance the derived function, but not all require the same permissive changes that occurred during history. We find that if evolution had begun from a different starting point within the network of sequences encoding the ancestral function, outcomes with different genetic and biochemical forms would probably have resulted; this contingency arises from the distribution of functional variants in sequence space and epistasis between residues. Our results illuminate the topology of the vast space of possibilities from which history sampled one path, highlighting how the outcome of evolution depends on a serial chain of compounding chance events.