Joseph W. Thornton

Evolution of vertebrate steroid receptors from an ancestral estrogen receptor by ligand exploitation and serial genome expansions

The evolution of novelty in tightly integrated biological systems, such as hormones and their receptors, seems to challenge the theory of natural selection: it has not been clear how a new function for any one part (such as a ligand) can be selected for unless the other members of the system (e.g., a receptor) are already present. Here I show—based on identification and phylogenetic analysis of steroid receptors in basal vertebrates and reconstruction of the sequences and functional attributes of ancestral proteins—that the first steroid receptor was an estrogen receptor, followed by a progesterone receptor. Genome mapping and phylogenetic analyses indicate that the full complement of mammalian steroid receptors evolved from these ancient receptors by two large-scale genome expansions, one before the advent of jawed vertebrates and one after. Specific regulation of physiological processes by androgens and corticoids are relatively recent innovations that emerged after these duplications. These findings support a model of ligand exploitation in which the terminal ligand in a biosynthetic pathway is the first for which a receptor evolves; selection for this hormone also selects for the synthesis of intermediates despite the absence of receptors, and duplicated receptors then evolve affinity for these substances. In this way, novel hormone-receptor pairs are created, and an integrated system of increasing complexity elaborated. This model suggests that ligands for some “orphan” receptors may be found among intermediates in the synthesis of ligands for phylogenetically related receptors.

Performance of maximum parsimony and likelihood phylogenetics when evolution is heterogeneous

All inferences in comparative biology depend on accurate estimates of evolutionary relationships. Recent phylogenetic analyses have turned away from maximum parsimony towards the probabilistic techniques of maximum likelihood and bayesian Markov chain Monte Carlo (BMCMC). These probabilistic techniques represent a parametric approach to statistical phylogenetics, because their criterion for evaluating a topology—the probability of the data, given the tree—is calculated with reference to an explicit evolutionary model from which the data are assumed to be identically distributed. Maximum parsimony can be considered nonparametric, because trees are evaluated on the basis of a general metric—the minimum number of character state changes required to generate the data on a given tree—without assuming a specific distribution. The shift to parametric methods was spurred, in large part, by studies showing that although both approaches perform well most of the time, maximum parsimony is strongly biased towards recovering an incorrect tree under certain combinations of branch lengths, whereas maximum likelihood is not. All these evaluations simulated sequences by a largely homogeneous evolutionary process in which data are identically distributed. There is ample evidence, however, that real-world gene sequences evolve heterogeneously and are not identically distributed. Here we show that maximum likelihood and BMCMC can become strongly biased and statistically inconsistent when the rates at which sequence sites evolve change non-identically over time. Maximum parsimony performs substantially better than current parametric methods over a wide range of conditions tested, including moderate heterogeneity and phylogenetic problems not normally considered difficult.

Structural analyses reveal phosphatidyl inositols as ligands for the NR5 orphan receptors SF-1 and LRH-1

Vertebrate members of the nuclear receptor NR5A subfamily, which includes steroidogenic factor 1 (SF-1) and liver receptor homolog 1 (LRH-1), regulate crucial aspects of development, endocrine homeostasis, and metabolism. Mouse LRH-1 is believed to be a ligand-independent transcription factor with a large and empty hydrophobic pocket. Here we present structural and biochemical data for three other NR5A members-mouse and human SF-1 and human LRH-1-which reveal that these receptors bind phosphatidyl inositol second messengers and that ligand binding is required for maximal activity. Evolutionary analysis of structure-function relationships across the SF-1/LRH-1 subfamily indicates that ligand binding is the ancestral state of NR5A receptors and was uniquely diminished or altered in the rodent LRH-1 lineage. We propose that phospholipids regulate gene expression by directly binding to NR5A nuclear receptors.

Crystal structure of an ancient protein: evolution by conformational epistasis.

The structural mechanisms by which proteins have evolved new functions are known only indirectly. We report x-ray crystal structures of a resurrected ancestral protein—the ∼450 million-year-old precursor of vertebrate glucocorticoid (GR) and mineralocorticoid (MR) receptors. Using structural, phylogenetic, and functional analysis, we identify the specific set of historical mutations that recapitulate the evolution of GRs hormone specificity from an MR-like ancestor. These substitutions repositioned crucial residues to create new receptor-ligand and intraprotein contacts. Strong epistatic interactions occur because one substitution changes the conformational position of another site. “Permissive” mutations—substitutions of no immediate consequence, which stabilize specific elements of the protein and allow it to tolerate subsequent function-switching changes—played a major role in determining GRs evolutionary trajectory.

Mechanistic approaches to the study of evolution: the functional synthesis.

An emerging synthesis of evolutionary biology and experimental molecular biology is providing much stronger and deeper inferences about the dynamics and mechanisms of evolution than were possible in the past. The new approach combines statistical analyses of gene sequences with manipulative molecular experiments to reveal how ancient mutations altered biochemical processes and produced novel phenotypes. This functional synthesis has set the stage for major advances in our understanding of fundamental questions in evolutionary biology. Here we describe this emerging approach, highlight important new insights that it has made possible, and suggest future directions for the field.

An epistatic ratchet constrains the direction of glucocorticoid receptor evolution.

The extent to which evolution is reversible has long fascinated biologists. Most previous work on the reversibility of morphological and life-history evolution has been indecisive, because of uncertainty and bias in the methods used to infer ancestral states for such characters. Further, despite theoretical work on the factors that could contribute to irreversibility, there is little empirical evidence on its causes, because sufficient understanding of the mechanistic basis for the evolution of new or ancestral phenotypes is seldom available. By studying the reversibility of evolutionary changes in protein structure and function, these limitations can be overcome. Here we show, using the evolution of hormone specificity in the vertebrate glucocorticoid receptor as a case-study, that the evolutionary path by which this protein acquired its new function soon became inaccessible to reverse exploration. Using ancestral gene reconstruction, protein engineering and X-ray crystallography, we demonstrate that five subsequent ‘restrictive’ mutations, which optimized the new specificity of the glucocorticoid receptor, also destabilized elements of the protein structure that were required to support the ancestral conformation. Unless these ratchet-like epistatic substitutions are restored to their ancestral states, reversing the key function-switching mutations yields a non-functional protein. Reversing the restrictive substitutions first, however, does nothing to enhance the ancestral function. Our findings indicate that even if selection for the ancestral function were imposed, direct reversal would be extremely unlikely, suggesting an important role for historical contingency in protein evolution.

Evolutionary biochemistry: revealing the historical and physical causes of protein properties

The repertoire of proteins and nucleic acids in the living world is determined by evolution; their properties are determined by the laws of physics and chemistry. Explanations of these two kinds of causality — the purviews of evolutionary biology and biochemistry, respectively — are typically pursued in isolation, but many fundamental questions fall squarely at the interface of fields. Here we articulate the paradigm of evolutionary biochemistry, which aims to dissect the physical mechanisms and evolutionary processes by which biological molecules diversified and to reveal how their physical architecture facilitates and constrains their evolution. We show how an integration of evolution with biochemistry moves us towards a more complete understanding of why biological molecules have the properties that they do.

Protein Evolution by Molecular Tinkering: Diversification of the Nuclear Receptor Superfamily from a Ligand- Dependent Ancestor

Phylogenetic reconstruction of the structure and function of the ancestor of the nuclear receptor protein family reveals how functional diversity evolves by subtle tinkering with an ancestral template.

Analyzing protein structure and function using ancestral gene reconstruction

Protein families with functionally diverse members can illuminate the structural determinants of protein function and the process by which protein structure and function evolve. To identify the key amino acid changes that differentiate one family member from another, most studies have taken a horizontal approach, swapping candidate residues between present-day family members. This approach has often been stymied, however, by the fact that shifts in function often require multiple interacting mutations; chimeric proteins are often nonfunctional, either because one lineage has amassed mutations that are incompatible with key residues that conferred a new function on other lineages, or because it lacks mutations required to support those key residues. These difficulties can be overcome by using a vertical strategy, which reconstructs ancestral genes and uses them as the appropriate background in which to study the effects of historical mutations on functional diversification. In this review, we discuss the advantages of the vertical strategy and highlight several exemplary studies that have used ancestral gene reconstruction to reveal the molecular underpinnings of protein structure, function, and evolution.

Evolution of increased complexity in a molecular machine

Many cellular processes are carried out by molecular ‘machines’—assemblies of multiple differentiated proteins that physically interact to execute biological functions. Despite much speculation, strong evidence of the mechanisms by which these assemblies evolved is lacking. Here we use ancestral gene resurrection and manipulative genetic experiments to determine how the complexity of an essential molecular machine—the hexameric transmembrane ring of the eukaryotic V-ATPase proton pump—increased hundreds of millions of years ago. We show that the ring of Fungi, which is composed of three paralogous proteins, evolved from a more ancient two-paralogue complex because of a gene duplication that was followed by loss in each daughter copy of specific interfaces by which it interacts with other ring proteins. These losses were complementary, so both copies became obligate components with restricted spatial roles in the complex. Reintroducing a single historical mutation from each paralogue lineage into the resurrected ancestral proteins is sufficient to recapitulate their asymmetric degeneration and trigger the requirement for the more elaborate three-component ring. Our experiments show that increased complexity in an essential molecular machine evolved because of simple, high-probability evolutionary processes, without the apparent evolution of novel functions. They point to a plausible mechanism for the evolution of complexity in other multi-paralogue protein complexes.