Experimental evolution of conflict mediation between genomes

Transitions to new levels of biological complexity often require cooperation among component individuals, but individual selection among those components may favor a selfishness that thwarts the evolution of cooperation. Biological systems with elements of cooperation and conflict are especially challenging to understand because the very direction of evolution is indeterminate and cannot be predicted without knowing which types of selfish mutations and interactions can arise. Here, we investigated the evolution of two bacteriophages (f1 and IKe) experimentally forced to obey a life cycle with elements of cooperation and conflict, whose outcome could have ranged from extinction of the population (due to selection of selfish elements) to extreme cooperation. Our results show the de novo evolution of a conflict mediation system that facilitates cooperation. Specifically, the two phages evolved to copackage their genomes into one protein coat, ensuring cotransmission with each other and virtually eliminating conflict. Thereafter, IKe evolved such extreme genome reduction that it lost the ability to make its own virions independent of f1. Our results parallel a variety of conflict mediation mechanisms existing in nature: evolution of reduced genomes in symbionts, cotransmission of partners, and obligate coexistence between cooperating species.     

War,space, and the evolution of Old World complex societies

How did human societies evolve from small groups, integrated by face-to-face cooperation, to huge anonymous societies of today, typically organized as states? Why is there so much variation in the ability of different human populations to construct viable states? Existing theories are usually formulated as verbal models and, as a result, do not yield sharply defined, quantitative predictions that could be unambiguously tested with data. Here we develop a cultural evolutionary model that predicts where and when the largest-scale complex societies arose in human history. The central premise of the model, which we test, is that costly institutions that enabled large human groups to function without splitting up evolved as a result of intense competition between societies—primarily warfare. Warfare intensity, in turn, depended on the spread of historically attested military technologies (e.g., chariots and cavalry) and on geographic factors (e.g., rugged landscape). The model was simulated within a realistic landscape of the Afroeurasian landmass and its predictions were tested against a large dataset documenting the spatiotemporal distribution of historical large-scale societies in Afroeurasia between 1,500 BCE and 1,500 CE. The model-predicted pattern of spread of large-scale societies was very similar to the observed one. Overall, the model explained 65% of variance in the data. An alternative model, omitting the effect of diffusing military technologies, explained only 16% of variance. Our results support theories that emphasize the role of institutions in state-building and suggest a possible explanation why a long history of statehood is positively correlated with political stability, institutional quality, and income per capita.Humans have the ability to live and cooperate in huge groups of genetically unrelated individuals (what can be termed “ultrasociality”) (1, 2). The central conceptual issue that this paper addresses is what mechanisms facilitate the spread of the necessary norms and institutions that enable human groups to function at the scale of millions of individuals (3–5). Social scientists have proposed a number of theories to explain the emergence of large-scale societies, emphasizing such factors as population growth, warfare, information management, economic specialization, and long-distance trade (6–10). However, because existing theories are usually formulated as verbal models, the causal mechanisms underlying these theories are not always made explicit. Understanding how ultrasocial norms and institutions spread is not a simple matter of their benefits for large-scale societies. Collective action problems, which stem from the tension between public nature of benefits yielded by cooperation and private costs borne by cooperating agents (11), inevitably arise when large groups of people need to cooperate in the production of public goods. Any theory that does not explain how societies find ways to solve these problems must be incomplete.     

Quantitative patterns of stylistic influence in the evolution of literature

Literature is a form of expression whose temporal structure, both in content and style, provides a historical record of the evolution of culture. In this work we take on a quantitative analysis of literary style and conduct the first large-scale temporal stylometric study of literature by using the vast holdings in the Project Gutenberg Digital Library corpus. We find temporal stylistic localization among authors through the analysis of the similarity structure in feature vectors derived from content-free word usage, nonhomogeneous decay rates of stylistic influence, and an accelerating rate of decay of influence among modern authors. Within a given time period we also find evidence for stylistic coherence with a given literary topic, such that writers in different fields adopt different literary styles. This study gives quantitative support to the notion of a literary "style of a time" with a strong trend toward increasingly contemporaneous stylistic influence.     

Toward a theory of evolution as multilevel learning

We apply the theory of learning to physically renormalizable systems in an attempt to outline a theory of biological evolution, including the origin of life, as multilevel learning. We formulate seven fundamental principles of evolution that appear to be necessary and sufficient to render a universe observable and show that they entail the major features of biological evolution, including replication and natural selection. It is shown that these cornerstone phenomena of biology emerge from the fundamental features of learning dynamics such as the existence of a loss function, which is minimized during learning. We then sketch the theory of evolution using the mathematical framework of neural networks, which provides for detailed analysis of evolutionary phenomena. To demonstrate the potential of the proposed theoretical framework, we derive a generalized version of the Central Dogma of molecular biology by analyzing the flow of information during learning (back propagation) and predicting (forward propagation) the environment by evolving organisms. The more complex evolutionary phenomena, such as major transitions in evolution (in particular, the origin of life), have to be analyzed in the thermodynamic limit, which is described in detail in the paper by Vanchurin et al. [V. Vanchurin, Y. I. Wolf, E. V. Koonin, M. I. Katsnelson, Proc. Natl. Acad. Sci. U.S.A. 119, 10.1073/pnas.2120042119 (2022)].

What is life? If this question is asked in the scientific rather than in the philosophical context, a satisfactory answer should assume the form of a theoretical model of the origin and evolution of complex systems that are identified with life (1). NASA has operationally defined life as follows: “Life is a self-sustaining chemical system capable of Darwinian evolution” (2, 3). Apart from the insistence on chemistry, long-term evolution that involves (random) mutation, diversification, and adaptation is, indeed, an intrinsic, essential feature of life that is not apparent in any other natural phenomena. The problem with this definition, however, is that natural (Darwinian) selection itself appears to be a complex rather than an elementary phenomenon (4). In all evolving organisms we are aware of, for natural selection to kick off and to sustain long-term evolution, an essential condition is replication of a complex digital information carrier (a DNA or RNA molecule). The replication fidelity must be sufficiently high to provide for the differential replication of emerging mutants and survival of the fittest ones (this replication fidelity level is often referred to as Eigen threshold) (5). In modern organisms, accurate replication is ensured by elaborate molecular machineries that include not only replication and repair enzymes but also, the entire metabolic network of the cell, which supplies energy and building blocks for replication. Thus, the origin of life is a typical chicken-and-egg problem (or catch-22); accurate replication is essential for evolution, but the mechanisms ensuring replication fidelity are themselves products of complex evolutionary processes (6, 7).Because genome replication that underlies natural selection is itself a product of evolution, origin of life has to be explained outside of the traditional framework of evolutionary biology. Modern evolutionary theory, steeped in population genetics, gives a detailed and arguably, largely satisfactory account of microevolutionary processes: that is, evolution of allele frequencies in a population of organisms under selection and random genetic drift (8, 9). However, this theory has little to say about the actual history of life, especially the emergence of new levels of biological complexity, and nothing at all about the origin of life.The crucial feature of biological complexity is its hierarchical organization. Indeed, multilevel hierarchies permeate biology: from small molecules to macromolecules; from macromolecules to functional complexes, subcellular compartments, and cells; from unicellular organisms to communities, consortia, and multicellularity; from simple multicellular organisms to highly complex forms with differentiated tissues; and from organisms to communities and eventually, to eusociality and to complex biocenoses involved in biogeochemical processes on the planetary scale. All these distinct levels jointly constitute the hierarchical organization of the biosphere. Understanding the origin and evolution of this hierarchical complexity, arguably, is one of the principal goals of biology.In large part, evolution of the multilevel organization of biological systems appears to be driven by solving optimization problems, which entails conflicts or trade-offs between optimization criteria at different levels or scales, leading to frustrated states, in the language of physics (10–12). Two notable cases in point are parasite–host arms races that permeate biological evolution and makes major contributions to the diversity and complexity of life-forms (13–16) and multicellular organization of complex organisms, where the tendency of individual cells to reproduce at the highest possible rate is countered by the control of cell division imposed at the organismal level (17, 18).Two tightly linked but distinct fundamental concepts that lie effectively outside the canonical narrative of evolutionary biology address evolution of biological complexity: major transitions in evolution (MTEs) (19–21) and multilevel selection (MLS) (22–27). Each MTE involves the emergence of a new level of organization, often described as an evolutionary transition in individuality. A clear-cut example is the evolution of multicellularity, whereby a new level of selection emerges, namely selection among ensembles of cells rather than among individual cells. Multicellular life-forms (even counting only complex organisms with multiple cell types) evolved on many independent occasions during the evolution of life (28, 29), implying that emergence of new levels of complexity is a major evolutionary trend rather than a rare, chance event.The MLS remains a controversial concept, presumably because of the link to the long-debated subject of group selection (27, 30). However, as a defining component of MTE, MLS appears to be indispensable. A proposed general mechanism behind the MTE, formulated by analogy with the physical theory of the origin of patterns (for example, in glass-like systems), involves competing interactions at different levels and the frustrated states, such interactions cause (12). In the physical theory of spin glasses, frustrations result in nonergodicity and enable formation and persistence of long-term memory: that is, history (31, 32). By contrast, ergodic systems have no true history because they reach all possible states during their evolution (at least in the large time limit), and thus, the only content of quasihistory of such systems is the transition from less probable to more probable states for purely combinatorial reasons: that is, entropy increase (33). As emphasized in Schroedinger’s seminal book (34), even if only in general terms, life is based on “negentropic” processes, and frustrations at different levels are necessary for these processes to take off and persist (12).The origin of cells, which can and probably should be equated with the origin of life, was the first and most momentous transition at the onset of biological evolution, and as such, it is outside the purview of evolutionary biology sensu stricto. Arguably, the theoretical investigation of the origin of life can be feasible only within the framework of an envelope theory that would incorporate biological evolution as a special case. It is natural to envisage such a theory as encompassing all nonergodic processes occurring in the universe, of which life is a special case, emerging under conditions that remain to be investigated and defined.Here, in pursuit of a maximally general theory of evolution, we adopt the formalism of the theory of machine learning (35). Importantly, learning here is perceived in the maximally general sense as an objective process that occurs in all evolving systems, including but not limited to biological ones (36). As such, the analogy between learning and selection appears obvious. Both types of processes involve trial and error and acceptance or rejection of the results based on some formal criteria; in other words, both are optimization processes (22, 37, 38). Here, we assess how far this analogy extends by establishing the correspondence between key features of biological evolution and concepts as well as the mathematical formalism of learning theory. We make the case that loss function, which is central to the learning theory, can be usefully and generally employed as the equivalent of the fitness function in the context of evolution. Our original motivation was to explain major features of biological evolution from more general principles of physics. However, after formulating such principles and embedding them within the mathematical framework of learning, we find that the theory can potentially apply to the entire history of the evolving universe (36), including physical processes that have been taking place since the big bang and chemical processes that directly antedated and set the stage for the origin of life. The central propositions of the evolution theory outlined here include both key physical principles (namely, hierarchy of scale, frequency gaps, and renormalizability) (39, 40) and major features of life (such as MLS, persistence of genetic parasites, and programmed cell death).We show that learning in a complex environment leads to separation of scales, with trainable variables splitting into at least two classes: faster- and slower-changing ones. Such separation of scales underlies all processes that involve the formation of complex structure in the universe from the scale of an atom to that of clusters of galaxies. We argue that, for the emergence of life, at least three temporal scales, which correspond to environmental, phenotypic, and genotypic variables, are essential. In evolving learning systems, the slowest-changing variables are digitized and acquire the replication capacity, resulting in differential reproduction depending on the loss (fitness) function value, which is necessary and sufficient for the onset of evolution by natural selection. Subsequent evolution of life involves emergence of many additional scales, which correspond to MTE. Hereafter, we use the term “evolution” to describe temporal changes of living and lifelike and prebiotic systems (organisms), whereas the more general term “dynamics” refers to temporal processes in other physical systems.At least since the publication of Schroedinger’s book, the possibility has been discussed that, although life certainly obeys the laws of physics, a different class of laws unique to biology could exist. Often, this putative physics of life is associated with emergence (41–43), but the nature of the involved emergent phenomena, to our knowledge, has not been clarified until very recently (36). Here, we outline a general approach to modeling and studying evolution as multilevel learning, supporting the view that a distinct type of physical theory, namely the theory of learning (35, 36), is necessary to investigate the evolution of complex objects in the universe, of which evolution of life is a specific, even if highly remarkable form.     

Rapid and widespread de novo evolution of kin discrimination

Diverse forms of kin discrimination, broadly defined as alteration of social behavior as a function of genetic relatedness among interactants, are common among social organisms from microbes to humans. However, the evolutionary origins and causes of kin-discriminatory behavior remain largely obscure. One form of kin discrimination observed in microbes is the failure of genetically distinct colonies to merge freely upon encounter. Here, we first use natural isolates of the highly social bacterium Myxococcus xanthus to show that colony-merger incompatibilities can be strong barriers to social interaction, particularly by reducing chimerism in multicellular fruiting bodies that develop near colony-territory borders. We then use experimental laboratory populations to test hypotheses regarding the evolutionary origins of kin discrimination. We show that the generic process of adaptation, irrespective of selective environment, is sufficient to repeatedly generate kin-discriminatory behaviors between evolved populations and their common ancestor. Further, we find that kin discrimination pervasively evolves indirectly between allopatric replicate populations that adapt to the same ecological habitat and that this occurs generically in many distinct habitats. Patterns of interpopulation discrimination imply that kin discrimination phenotypes evolved via many diverse genetic mechanisms and mutation-accumulation patterns support this inference. Strong incompatibility phenotypes emerged abruptly in some populations but strengthened gradually in others. The indirect evolution of kin discrimination in an asexual microbe is analogous to the indirect evolution of reproductive incompatibility in sexual eukaryotes and linguistic incompatibility among human cultures, the commonality being indirect, noncoordinated divergence of complex systems evolving in isolation.The behavior of many vertebrates (1, 2), invertebrates (3, 4) and microbes (5–7), as well as some plants (8), is altered by social encounters with conspecifics in a relatedness-dependent manner. Such kin discrimination is commonly interpreted in the context of inclusive fitness theory to have resulted from positive selection for kin discrimination per se (7, 9–11) specifically because such discrimination promotes preferential cooperation among kin that share cooperation alleles (12–14). However, despite any theoretical plausibility of kin selectionist explanations, the actual evolutionary origins of kin discrimination in natural populations are often difficult to infer due to their temporal remove (11, 15). Kin discrimination, broadly defined (SI Appendix, Methods), might also arise indirectly as a byproduct of alternative evolutionary forces (15–20). Despite decades of rigorous empirical and theoretical investigation of kin discrimination and its causes, a biological system that allows both the documentation of kin discrimination origins and causally proximate analysis of the evolutionary forces responsible for those origins has been lacking.Among motile microbes, one form of biological kin discrimination is reduced merger of genetically distinct swarming colonies upon encounter relative to “self–self” controls. This phenomenon was first documented in 1946 with the observation of “Dienes lines” that formed between distinct nonmerging colonies of the bacterium Proteus mirabilis (21) and has since been found in several other species (20, 22). For example, a large number of such colony-merger incompatibilities evolved among closely related genotypes of the cooperative bacterium Myxococcus xanthus in a natural centimeter-scale population (20). Irrespective of their original evolutionary cause(s), the emergence of colony-merger incompatibilities in nature is likely to have profound implications for the distribution of social interactions among genotypes during cooperative processes. For example, barriers to colony merger may promote the maintenance of genotypes that are inferior social competitors in chimeric groups and promote cooperation by hindering the territorial spread of socially defective cheaters (20), as might other forms of kin discrimination (23).In this study, we first use natural isolates of M. xanthus to test whether kin discrimination affects patterns of cooperation during fruiting body development when migrating social groups encounter one another. To do so, we quantify the frequency of chimerism among fruiting bodies that form near the border of colony territories, both for pairings of distinct colony-merger allotypes and self–self controls. Subsequently, we use experimentally evolved laboratory populations to test whether (i) generic adaptation by migrating populations (irrespective of variable selective conditions) tends to generate colony-merger incompatibilities toward an ancestral genotype and (ii) whether mere independence of the adaptive process causes allopatric populations to evolve trait differences that generate kin discrimination phenotypes upon secondary contact. We also characterize temporal patterns of kin discrimination evolution and test whether kin discrimination evolved by one or rather multiple molecular mechanisms.     

Evolutionary constraints to viroid evolution

We suggest that viroids are trapped into adaptive peaks as the result of adaptive constraints. The first one is imposed by the necessity to fold into packed structures to escape from RNA silencing. This creates antagonistic epistases, which make future adaptive trajectories contingent upon the first mutation and slow down the rate of adaptation. This second constraint can only be surpassed by increasing genetic redundancy or by recombination. Eigen's paradox imposes a limit to the increase in genome complexity in the absence of mechanisms reducing mutation rate. Therefore, recombination appears as the only possible route to evolutionary innovation in viroids.     

Nonlinear detection of paleoclimate-variability transitions possibly related to human evolution

Potential paleoclimatic driving mechanisms acting on human evolution present an open problem of cross-disciplinary scientific interest. The analysis of paleoclimate archives encoding the environmental variability in East Africa during the past 5 Ma has triggered an ongoing debate about possible candidate processes and evolutionary mechanisms. In this work, we apply a nonlinear statistical technique, recurrence network analysis, to three distinct marine records of terrigenous dust flux. Our method enables us to identify three epochs with transitions between qualitatively different types of environmental variability in North and East Africa during the (i) Middle Pliocene (3.35–3.15 Ma B.P.), (ii) Early Pleistocene (2.25–1.6 Ma B.P.), and (iii) Middle Pleistocene (1.1–0.7 Ma B.P.). A deeper examination of these transition periods reveals potential climatic drivers, including (i) large-scale changes in ocean currents due to a spatial shift of the Indonesian throughflow in combination with an intensification of Northern Hemisphere glaciation, (ii) a global reorganization of the atmospheric Walker circulation induced in the tropical Pacific and Indian Ocean, and (iii) shifts in the dominating temporal variability pattern of glacial activity during the Middle Pleistocene, respectively. A reexamination of the available fossil record demonstrates statistically significant coincidences between the detected transition periods and major steps in hominin evolution. This result suggests that the observed shifts between more regular and more erratic environmental variability may have acted as a trigger for rapid change in the development of humankind in Africa.     

Experimental evolution of selfish policing in social bacteria

Cooperative organisms evolve within socially diverse populations. In populations harboring both cooperators and cheaters, cooperators might adapt by evolving novel interactions with either social type or both. Diverse animal traits suppress selfish behaviors when cooperation is important for fitness, but the potential for prokaryotes to evolve such traits is unclear. We allowed a strain of the bacterium Myxococcus xanthus that is proficient at cooperative fruiting body development to evolve while repeatedly encountering a non-evolving developmental cheater. Evolving populations greatly increased their fitness in the presence of the cheater, both relative to their ancestor and in terms of absolute spore productivity. However, the same evolved lineages exhibited a net disadvantage to the ancestor in the cheater's absence. Evolving populations reversed a large ancestral disadvantage to the cheater into competitive superiority and also evolved to strongly suppress cheater productivity. Moreover, in three-party mixes with the cheater, evolved populations enhanced their ancestor's productivity relative to mixes of only the ancestor and cheater. Thus, our evolved populations function as selfish police that inhibit cheaters, both to their own advantage and to the benefit of others as well. Cheater suppression was general across multiple unfamiliar cheaters but was more pronounced against the evolutionarily familiar cheater. Also, evolution generated three new mutually beneficial relationships, including complementary defect rescue between evolved cells and the selection-regime cheater. The rapid evolution of cheater suppression documented here suggests that coevolving social strategies within natural populations of prokaryotes are more diverse and complex than previously appreciated.     

Experimental interrogation of the path dependence and stochasticity of protein evolution using phage-assisted continuous evolution

To what extent are evolutionary outcomes determined by a population''s recent environment, and to what extent do they depend on historical contingency and random chance? Here we apply a unique experimental system to investigate evolutionary reproducibility and path dependence at the protein level. We combined phage-assisted continuous evolution with high-throughput sequencing to analyze evolving protein populations as they adapted to divergent and then convergent selection pressures over hundreds of generations. Independent populations of T7 RNA polymerase genes were subjected to one of two selection histories (“pathways”) demanding recognition of distinct intermediate promoters followed by a common final promoter. We observed distinct classes of solutions with unequal phenotypic activity and evolutionary potential evolve from the two pathways, as well as from replicate populations exposed to identical selection conditions. Mutational analysis revealed specific epistatic interactions that explained the observed path dependence and irreproducibility. Our results reveal in molecular detail how protein adaptation to different environments, as well as stochasticity among populations evolved in the same environment, can both generate evolutionary outcomes that preclude subsequent convergence.     

Climate change and state evolution

Despite the vast evidence on the short-run effects of adverse climate shocks on the economy, our understanding of their long-run impact on institutions is limited. To tackle such a key issue, a vast body of research has focused on ancient societies because of the limited complexity of their economies and their unparalleled experience with environmental and institutional change. Notably, the “collapse archaeology” literature has reported countless correlations consistent with the mantra that severe droughts are bound to trigger institutional crises. This conclusion, however, has been recently challenged by a stream of papers that, building on more detailed data on Bronze Age Mesopotamia and a more credible theory-based empirical strategy, have yielded the following two results. First, severe droughts pushed the elites to grant strong political and property rights to the nonelites to convince them that a sufficient part of the returns on joint investments would be shared via public good provision and, thus, to cooperate and accumulate a culture of cooperation. Second, a more favorable climate allowed the elites to elicit cooperation under less inclusive political regimes as well as a weaker culture of cooperation and, possibly, incomplete property rights. These patterns emphasize the importance of considering the asymmetric effect of droughts and, more generally, combining natural and social sciences for the evaluation of climate-related policies.     

Bacterial marginolactones trigger formation of algal gloeocapsoids,protective aggregates on the verge of multicellularity

Photosynthetic microorganisms including the green alga Chlamydomonas reinhardtii are essential to terrestrial habitats as they start the carbon cycle by conversion of CO₂ to energy-rich organic carbohydrates. Terrestrial habitats are densely populated, and hence, microbial interactions mediated by natural products are inevitable. We previously discovered such an interaction between Streptomyces iranensis releasing the marginolactone azalomycin F in the presence of C. reinhardtii. Whether the alga senses and reacts to azalomycin F remained unknown. Here, we report that sublethal concentrations of azalomycin F trigger the formation of a protective multicellular structure by C. reinhardtii, which we named gloeocapsoid. Gloeocapsoids contain several cells which share multiple cell membranes and cell walls and are surrounded by a spacious matrix consisting of acidic polysaccharides. After azalomycin F removal, gloeocapsoid aggregates readily disassemble, and single cells are released. The presence of marginolactone biosynthesis gene clusters in numerous streptomycetes, their ubiquity in soil, and our observation that other marginolactones such as desertomycin A and monazomycin also trigger the formation of gloeocapsoids suggests a cross-kingdom competition with ecological relevance. Furthermore, gloeocapsoids allow for the survival of C. reinhardtii at alkaline pH and otherwise lethal concentrations of azalomycin F. Their structure and polysaccharide matrix may be ancestral to the complex mucilage formed by multicellular members of the Chlamydomonadales such as Eudorina and Volvox. Our finding suggests that multicellularity may have evolved to endure the presence of harmful competing bacteria. Additionally, it underlines the importance of natural products as microbial cues, which initiate interesting ecological scenarios of attack and counter defense.

Soil is an extremely densely populated habitat, and hence, microbial interactions are nearly inevitable (1). Green algae are often overlooked when soil ecosystems are discussed despite their pivotal role as primary producers of organic carbohydrates fixing roughly 39 g carbon per square meter of soil per year (2, 3). As photosynthetic microorganisms, algae convert CO₂ to energy-rich organic carbon sources and thereby refuel the carbon cycle. The green alga Chlamydomonas reinhardtii is a common member of wet soils and is hence subject to biotic and abiotic stress (2, 4, 5). Stress leads to the development of adaptive mechanisms that enable survival and increase the evolutionary fitness of microorganisms. Chlamydomonas spp. react to NaCl stress (6), Ca²⁺ deprivation, ethylenediaminetetraacetic acid (EDTA), organic acids (7, 8), chloroplatinic acid (9), phosphate limitation (10), acidic pH (11), and sublethal levels of pollutants (12) with the production of palmelloids, which are characterized by multiple rounds of failure of daughter cells to escape the parental cell wall after cell division. Chlorella vulgaris forms palmelloids when treated with ecdysteroids (13). The term palmelloid is a catch-all term that originates in reference to the genus of green algae Palmella, which typically grows in a cell cluster (6, 14). Chlamydomonas spp. can also actively produce aggregates which are phenotypically different to palmelloids and serve to defend the algae against harsh stress (14–16).In addition to abiotic stressors, there are also biotic stressors such as competition and predation. When C. reinhardtii is threatened by the rotifer predator Brachionus calyciflorus, the green alga forms palmelloids (17). Paramecium tetraurelia is also a predator of C. reinhardtii, which likely drove the evolution of C. reinhardtii into multicellular aggregates in response to this constant pressure by predation (18). Palmelloid aggregates are too big in diameter to be engulfed by P. tetraurelia and thus are protected. Another biotic stress is exerted by natural products, low molecular mass compounds with various biological activities often produced by neighboring microorganisms (19). For instance, the bacterium Pseudomonas protegens produces the cyclic lipopeptide orfamide A, which leads to the deflagellation of C. reinhardtii (20). Other microorganisms accompanying algae in wet soils are streptomycetes, known to be prolific producers of natural products (1). These filamentous bacteria are known to readily interact with other microorganisms. A well-known example is given by Streptomyces iranensis that induces otherwise silent natural product biosynthesis gene clusters in the fungi Aspergillus nidulans and Aspergillus fumigatus (21, 22). The products of A. nidulans, orsellinic acid, and lecanoric acid represent metabolites first described in lichens (23). A. fumigatus reacts to the streptomycete by the production of fumigermin, which inhibits the germination of spores of several Streptomyces species (22). However, these interactions are not exclusive to fungi but also include algae. Recently, we demonstrated that S. iranensis specifically released the algicidal marginolactone azalomycin F (SI Appendix, Fig. 1A) in the presence of C. reinhardtii. The alga survived this attack by taking shelter in the mycelium of A. nidulans (24). Whether the alga senses azalomycin F and reacts to the compound remained unknown. Here, we describe the discovery of an alternative strategy for the algae to cope with toxin stress without a fungal partner: the formation of so-called gloeocapsoids, a distinct type of palmelloids differing in function and based on a close resemblance of the gloeocapsoid structure to cyanobacteria of the genera Gloeocapsa and Gloeothece (25). We propose that gloeocapsoid formation is an active protective behavior induced by membrane-targeting marginolactones like azalomycin F, desertomycin A, and monazomycin. Additionally, we propose that the formation of transient cell aggregates like gloeocapsoids could have led to the evolution of multicellular green algae such as Eudorina and Volvox.     

Eukaryogenesis,how special really?

Eukaryogenesis is widely viewed as an improbable evolutionary transition uniquely affecting the evolution of life on this planet. However, scientific and popular rhetoric extolling this event as a singularity lacks rigorous evidential and statistical support. Here, we question several of the usual claims about the specialness of eukaryogenesis, focusing on both eukaryogenesis as a process and its outcome, the eukaryotic cell. We argue in favor of four ideas. First, the criteria by which we judge eukaryogenesis to have required a genuinely unlikely series of events 2 billion years in the making are being eroded by discoveries that fill in the gaps of the prokaryote:eukaryote “discontinuity.” Second, eukaryogenesis confronts evolutionary theory in ways not different from other evolutionary transitions in individuality; parallel systems can be found at several hierarchical levels. Third, identifying which of several complex cellular features confer on eukaryotes a putative richer evolutionary potential remains an area of speculation: various keys to success have been proposed and rejected over the five-decade history of research in this area. Fourth, and perhaps most importantly, it is difficult and may be impossible to eliminate eukaryocentric bias from the measures by which eukaryotes as a whole are judged to have achieved greater success than prokaryotes as a whole. Overall, we question whether premises of existing theories about the uniqueness of eukaryogenesis and the greater evolutionary potential of eukaryotes have been objectively formulated and whether, despite widespread acceptance that eukaryogenesis was “special,” any such notion has more than rhetorical value.     

Molecular evolution of peptidergic signaling systems in bilaterians

Peptide hormones and their receptors are widespread in metazoans, but the knowledge we have of their evolutionary relationships remains unclear. Recently, accumulating genome sequences from many different species have offered the opportunity to reassess the relationships between protostomian and deuterostomian peptidergic systems (PSs). Here we used sequences of all human rhodopsin and secretin-type G protein-coupled receptors as bait to retrieve potential homologs in the genomes of 15 bilaterian species, including nonchordate deuterostomian and lophotrochozoan species. Our phylogenetic analysis of these receptors revealed 29 well-supported subtrees containing mixed sets of protostomian and deuterostomian sequences. This indicated that many vertebrate and arthropod PSs that were previously thought to be phyla specific are in fact of bilaterian origin. By screening sequence databases for potential peptides, we then reconstructed entire bilaterian peptide families and showed that protostomian and deuterostomian peptides that are ligands of orthologous receptors displayed some similarity at the level of their primary sequence, suggesting an ancient coevolution between peptide and receptor genes. In addition to shedding light on the function of human G protein-coupled receptor PSs, this work presents orthology markers to study ancestral neuron types that were probably present in the last common bilaterian ancestor.In animals the regulation of complex homeostatic processes and their behavioral output relies on the modulation of neuronal activity in well-defined circuits of the brain. Groups of neurons can influence the activity of other groups of neurons by releasing in the extracellular milieu short peptide hormones, called neuropeptides, which, with few exceptions, notably insulin-like peptides, bind G protein-coupled receptors (GPCRs) that are expressed at the surface of target cells. GPCRs are seven-pass membrane receptors that can bind to a wide variety of ligands (1) and form the largest family of integral membrane proteins in the human genome (2). The majority of GPCRs that are activated by peptide ligands are thought to be evolutionarily related and belong to the rhodopsin β and γ classes of rhodopsin (r) GPCRs, or to the secretin (s) family of GPCRs (3). Peptides are short (<40 amino acids) secreted polypeptides derived from larger precursor proteins that are encoded by the genome and processed by specialized enzymes (4). They share defining features at the level of their primary sequence, including the presence of signal peptides at their N terminus, of canonical dibasic processing sites that are recognized by prohormone convertase cleaving enzymes (5), and of a C-terminal glycine that is the target of amidation enzymes (6).Research on peptide hormones has a long history (7, 8), and during the last decades a substantial number of peptide–receptors systems, or peptidergic systems (PSs), have been characterized by reverse pharmacology methods in both insects (9) and mammals (10). In parallel, the first genome sequencing projects have enhanced our knowledge of PS diversity in protostomian species, notably in the fly Drosophila melanogaster (11), the nematode Caenorhabditis elegans (12), and the mosquito Anopheles gambiae (13). In these species, original genome-wide searches have revealed the existence of a large number of GPCRs that resembled vertebrate GPCRs (11), but comparatively few vertebrate-type peptides (11, 12, 14).Before the genomic era, some researchers had postulated a deep orthology between PSs from distant animals on the basis of peptide primary sequence similarity (15), functional analogies (16), and immunoreactivity of invertebrate tissues to mammalian hormone antibodies (17), but the idea that it could be a general feature of PSs remained controversial. Now, with the accumulation of molecular sequence data and the characterization of a growing number of PSs from insects and mammals, the concept of a bona fide orthology between protostome and deuterostome PSs has garnered new support (18, 19). Recently, Schoofs and coworkers have added new weight to this theory by showing that some arthropod-type PSs [adipokinetic hormone (AKH), pyrokinin (PK), and sulfakinin (SK)] occurring in C. elegans were orthologous to vertebrate PSs [gonadoliberin (GnRH), neuromedin U (NMU), and cholecystokinin (CCK)] (20–22).In an effort to clarify the relationships between protostomian and deuterostomian PSs, we set out to reconstruct the full evolutionary history of bilaterian peptide and receptor genes. We used data from publicly available genomes from Ensembl (23), the Joint Genome Institute (JGI) (24), the Ghost database (25), and the Baylor College of Medicine (BCM), including data from key lophotrochozoan and ambulacrarian phyla that are thought to have retained ancestral features of the bilaterian brain (26–28). We performed phylogenetic reconstructions (29, 30) and used a hidden Markov model (HMM)-based program, which predicts precursor hormone sequences (31).Our analysis suggests that 29 PSs were present in the last common ancestor of bilaterians (the urbilaterian) and that, in the general case, peptide and receptor genes coevolved in the different lineages leading to present-day bilaterians. We present a comprehensive list of PSs that are common to bilaterian species, so that these orthology markers can be used to reveal the origin and function of ancient peptidergic cell types and circuits. All sequences, phylogenetic trees, and annotations derived from these analyses can be found at http://neuroevo.org.     

Unraveling the evolution of uniquely human cognition

A satisfactory account of human cognitive evolution will explain not only the psychological mechanisms that make our species unique, but also how, when, and why these traits evolved. To date, researchers have made substantial progress toward defining uniquely human aspects of cognition, but considerably less effort has been devoted to questions about the evolutionary processes through which these traits have arisen. In this article, I aim to link these complementary aims by synthesizing recent advances in our understanding of what makes human cognition unique, with theory and data regarding the processes of cognitive evolution. I review evidence that uniquely human cognition depends on synergism between both representational and motivational factors and is unlikely to be accounted for by changes to any singular cognitive system. I argue that, whereas no nonhuman animal possesses the full constellation of traits that define the human mind, homologies and analogies of critical aspects of human psychology can be found in diverse nonhuman taxa. I suggest that phylogenetic approaches to the study of animal cognition—which can address questions about the selective pressures and proximate mechanisms driving cognitive change—have the potential to yield important insights regarding the processes through which the human cognitive phenotype evolved.     

From the Cover: Model of genetic variation in human social networks

Social networks exhibit strikingly systematic patterns across a wide range of human contexts. Although genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here, we show that 3 of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a “mirror network” method to test extant network models and show that none account for observed genetic variation in human social networks. We propose an alternative “Attract and Introduce” model with two simple forms of heterogeneity that generates significant heritability and other important network features. We show that the model is well suited to real social networks in humans. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person.     

Experimental evolution of prepared learning

Animals learn some things more easily than others. To explain this so-called prepared learning, investigators commonly appeal to the evolutionary history of stimulus–consequence relationships experienced by a population or species. We offer a simple model that formalizes this long-standing hypothesis. The key variable in our model is the statistical reliability of the association between stimulus, action, and consequence. We use experimental evolution to test this hypothesis in populations of Drosophila. We systematically manipulated the reliability of two types of experience (the pairing of the aversive chemical quinine with color or with odor). Following 40 generations of evolution, data from learning assays support our basic prediction: Changes in learning abilities track the reliability of associations during a population’s selective history. In populations where, for example, quinine–color pairings were unreliable but quinine–odor pairings were reliable, we find increased sensitivity to learning the quinine–odor experience and reduced sensitivity to learning quinine–color. To the best of our knowledge this is the first experimental demonstration of the evolution of prepared learning.For animals to learn, they must form associations among various stimuli. However, in a world full of potential stimuli, why does a special relationship form between a given stimulus and consequence in a way that actually allows the animal to predict future events? Animals seem to solve this problem by being born better able to learn some things than others. The most notable example of this special learning is the Garcia effect, published in one of the most influential papers in the history of animal learning (1). This paper showed that rats are prepared to learn some associations (e.g., taste and gastric illness) and less well prepared to learn others (e.g., light–sound combinations and gastric illness). In its day, this evidence was seen as both important and controversial, because it challenged the prevailing claims about the generality of the learning process [specifically the idea of equipotentiality (e.g., 2–6)]. We now have many examples of preparedness in learning (e.g., 5–8), although the terms used to describe this phenomenon have varied widely. Investigators have called this “belongingness” (9), species-specific defense reactions (10), biological constraints (e.g., 5, 11), adaptive specializations (8), and “preparedness” (4, 12). In response, learning theorists have advocated more general theories of learning that acknowledge an element of biological preparedness in nearly all learning (13–17).Investigators seem to agree that the explanation of preparedness must flow from evolution. Evolution by natural selection, the argument goes, has prepared animals to learn from some associations better than others because these associations had predictive power in the animal’s evolutionary past. However, within this agreed framework, explanations of specific examples of prepared learning tend to be post hoc and glib, in that we identify the “predictive power” of specific associations only after investigators have identified an example of prepared learning. Taste obviously predicts the onset of gastric illness more reliably than flashing lights, after we have Garcia''s result in hand. In response to this unsatisfying situation, several authors have argued that the study of preparedness needs a clear-cut predictive theory (3, 18, 19). Without such a predictive theory to guide them, investigators seem to have lost interest in further empirical studies of preparedness (see refs. 20–23 for possible exceptions to this pattern).Even with an agreed conceptual framework in hand, studies of the evolution of preparedness face a significant empirical hurdle. The problem is that any model of the evolution of preparedness will flow from properties of the environment that the animal’s ancestors experienced during the course of evolution. How can we know empirically whether tastes have reliably predicted gastric illness since the Paleozoic? A meaningful test of claims like this would seem to require a time machine.This paper addresses these two problems directly. First, it offers a simple model that formalizes existing ideas about the evolution of prepared learning in terms of measureable and experimentally accessible variables. Second, and most important, it uses the techniques of experimental evolution to create a selective environment in which stimuli, actions, and consequences have specific and controlled statistical relationships as our model of preparedness requires.     

The experimental evolution of aging in fruitflies

—The evolutionary theory of aging suggests that the level of repair will evolve to an intermediate optimum that permits the accumulation of random damage to cells. This, in turn, causes a decline in essential functions during the life span of an organism. The central claim of the life history theory of aging is that intrinsic mortality rates evolve in response to changes in extrinsic mortality rates. To prove this central claim, it must be evaluated experimentally. Experimental evolution is an approach that has been yielding interesting results from both a variety of questions posed and organisms examined. In this article the organism chosen for study is the fruitfly (Drosophilia melanogaster) in which the evolutionary effects of high and low adult mortality rates are compared. It has been found that higher extrinsic mortality rates lead to the evolution of higher intrinsic mortality rates and a shorter life span. This is the first clear experimental demonstration of the central claim of the evolutionary theory of aging.