Coevolution between predator and prey plays a central role in shaping the pelagic realm and may have significant implications for marine ecosystems and nutrient cycling dynamics. The siliceous diatom frustule is often assumed to have coevolved with the silica-lined teeth of copepods, but empirical evidence of how this relationship drives natural selection and evolution is still lacking. Here, we show that feeding on diatoms causes significant wear and tear on copepod teeth and that this leads to copepods becoming selective feeders. Teeth from copepods feeding on thick-shelled diatoms were more likely to be broken or cracked than those feeding on a dinoflagellate. When fed a large diatom, all analyzed teeth had visible wear. Our results underscore the importance of the predator-prey arms race as a driving force in planktonic evolution and diversity.

Epidemic models study the spread of undesired agents through populations, be it infectious diseases through a country, misinformation in social media or pests infesting a region. In combating these epidemics, we rely neither on global top-down interventions, nor solely on individual adaptations. Instead, interventions commonly come from local institutions such as public health departments, moderation teams on social media platforms or other forms of group governance. Classic models, which are often individual or agent-based, are ill-suited to capture local adaptations. We leverage developments of institutional dynamics based on cultural group selection to study how groups attempt local control of an epidemic by taking inspiration from the successes and failures of other groups. Incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation. When groups perceive a contagion as more worrisome, they can invest in improved policies and, if they maintain these policies long enough to have impact, lead to a reduction in endemicity. By looking at the interplay between the speed of institutions and the transmission rate of the contagions, we find rich coevolutionary dynamics that reflect the complexity of known biological and social contagions.

Plants are unique organisms that have developed ingenious strategies to cope with environmental challenges, such as herbivorous insects. One of these strategies is the synthesis of a vast array of chemical compounds, known as specialized metabolites, that serve many ecological functions. Among the most fascinating and diverse groups of specialized metabolites are the alkaloids, which are characterized by the presence of a nitrogen atom within a heterocyclic ring. While some have medicinal and recreational applications, others are highly unpalatable and/or toxic. The effects of alkaloids on both humans and insects can be very diverse, affecting their physiology and behavior. Insects that feed on alkaloid-containing plants have evolved diverse mechanisms to cope with the consequences of these toxins. These include sequestration, where insects store alkaloids in specialized tissues or organs, enzymatic detoxification through enzymes such as cytochrome P450 monooxygenases and glutathione S-transferases, and behavioral adaptations such as selective feeding. In this review, we explore the relationships between plant alkaloids and the evolutionary adaptations that enable insects to exploit alkaloid-rich plants as food sources and ecological niches minimizing the harmful effects of these natural compounds. We aim to provide a comprehensive and updated overview of this fascinating and complex ecological interaction.

Herbarium specimens are increasingly being used as sources of information to understand the ecology and evolution of plants and their associated microbes. Most studies have used specimens as a source of genetic material using culture-independent approaches. We demonstrate that herbarium specimens can also be used to culture nodule-associated bacteria, opening the possibility of using specimens to understand plant-microbe interactions at new spatiotemporal scales. We used historic and contemporary nodules of a common legume, Medicago lupulina, to create a culture collection. We were able to recover historic bacteria in 15 genera from three specimens (collected in 1950, 2004, and 2015). This work is the first of its kind to isolate historic bacteria from herbarium specimens. Future work should include inoculating plants with historic strains to see if they produce nodules and if they affect plant phenotype and fitness. Although we were unable to recover any Ensifer, the main symbiont of Medicago lupulina, we recovered some other potential nodulating species, as well as many putative growth-promoting bacteria.

Social relations are embedded in material, cultural, and institutional settings that affect network dynamics and the resulting topologies. For example, romantic entanglements are subject to social and cultural norms, interfirm alliances are constrained by country-specific legislation, and adolescent friendships are conditioned by classroom settings and neighborhood effects. In short, social contexts shape social relations and the networks they give rise to. However, how and when they do so remain to be established. This paper presents network ecology as a general framework for identifying how the proximal environment shapes social networks by focusing interactions and social relations, and how these interactions and relations in turn shape the environment in which social networks form. Tie fitness is introduced as a metric that quantifies how well particular dyadic social relations would align with the setting. Using longitudinal networks collected on two cohorts each in 18 North American schools, i.e., 36 settings, we develop five generalizable observations about the time-varying fitness of adolescent friendship. Across all 252 analyzed networks, tie fitness predicted new tie formation, tie longevity, and tie survival. Dormant fit ties cluster in relational niches, thereby establishing a resource base for social identities competing for increased representation in the relational system.

Comparative analyses of gene birth-death dynamics have the potential to reveal gene families that played an important role in the evolution of morphological, behavioral, or physiological variation. Here, we used whole genomes of 30 species of butterflies and moths to identify gene birth-death dynamics among the Lepidoptera that are associated with specialist or generalist feeding strategies. Our work advances this field using a uniform set of annotated proteins for all genomes, investigating associations while correcting for phylogeny, and assessing all gene families rather than a priori subsets. We discovered that the sizes of several important gene families (e.g. those associated with pesticide resistance, xenobiotic detoxification, and/or protein digestion) are significantly correlated with diet breadth. We also found 22 gene families showing significant shifts in gene birth-death dynamics at the butterfly (Papilionoidea) crown node, the most notable of which was a family of pheromone receptors that underwent a contraction potentially linked with a shift to visual-based mate recognition. Our findings highlight the importance of uniform annotations, phylogenetic corrections, and unbiased gene family analyses in generating a list of candidate genes that warrant further exploration.

The iconic Monarch butterfly is probably the best-known example of chemical defence against predation, as pictures of vomiting naive blue jays in countless textbooks vividly illustrate. Larvae of the butterfly take up toxic cardiac glycosides from their milkweed hostplants and carry them over to the adult stage. These compounds (cardiotonic steroids, including cardenolides and bufadienolides) inhibit the animal transmembrane sodium-potassium ATPase (Na,K-ATPase), but the Monarch enzyme resists this inhibition thanks to amino acid substitutions in its catalytic alpha-subunit. Some birds also have substitutions and can feast on cardiac glycoside-sequestering insects with impunity. A flurry of recent work has shown how the alpha-subunit gene has been duplicated multiple times in separate insect lineages specializing in cardiac glycoside-producing plants. In this issue of Molecular Ecology, Herbertz et al. toss the beta-subunit into the mix, by expressing all nine combinations of three alpha- and three beta-subunits of the milkweed bug Na,K-ATPase and testing their response to a cardenolide from the hostplant. The findings suggest that the diversification and subfunctionalization of genes allow milkweed bugs to balance trade-offs between resistance towards sequestered host plant toxins that protect the bugs from predators, and physiological costs in terms of Na,K-ATPase activity.

Male seminal fluid proteins often show signs of positive selection and divergent evolution, believed to reflect male-female coevolution. Yet, our understanding of the predicted concerted evolution of seminal fluid proteins and female reproductive proteins is limited. We sequenced, assembled, and annotated the genome of two species of seed beetles allowing a comparative analysis of four closely related species of these herbivorous insects. We compare the general pattern of evolution in genes encoding seminal fluid proteins and female reproductive proteins with those in digestive protein genes and well-conserved reference genes. We found that female reproductive proteins showed an overall ratio of nonsynonymous to synonymous substitutions (ω) similar to that of conserved genes, while seminal fluid proteins and digestive proteins exhibited higher overall ω values. Further, seminal fluid proteins and digestive proteins showed a higher proportion of sites putatively under positive selection, and explicit tests showed no difference in relaxed selection between protein types. Evolutionary rate covariation analyses showed that evolutionary rates among seminal fluid proteins were on average more closely correlated with those in female reproductive proteins than with either digestive or conserved genes. Gene expression showed the expected negative covariation with ω values, except for male-biased genes where this negative relationship was reversed. In conclusion, seminal fluid proteins showed relatively rapid evolution and signs of positive selection. In contrast, female reproductive proteins evolved at a lower rate under selective constraints, on par with genes known to be well conserved. Although our findings provide support for concerted evolution of seminal fluid proteins and female reproductive proteins, they also suggest that these two classes of proteins evolve under partly distinct selective regimes.

In the SARS-CoV-2 lineage, RNA elements essential for its viral life cycle, including genome replication and gene expression, have been identified. Still, the precise structures and functions of these RNA regions in coronaviruses remain poorly understood. This lack of knowledge points out the need for further research to better understand these crucial aspects of viral biology and, in time, prepare for future outbreaks. In this research, the in silico analysis of the cis RNA structures that act in the alpha-, beta-, gamma-, and deltacoronavirus genera has provided a detailed view of the presence and adaptation of the structures of these elements in coronaviruses. The results emphasize the importance of these cis elements in viral biology and their variability between different viral variants. Some coronavirus variants in some groups, depending on the cis element (stem-loop1 and -2; pseudoknot stem-loop1 and -2, and s2m), exhibited functional adaptation. Additionally, the conformation flexibility of the s2m element in the SARS variants was determined, suggesting a coevolution of this element in this viral group. The variability in secondary structures suggests genomic adaptations that may be related to replication processes, genetic regulation, as well as the specific pathogenicity of each variant. The results suggest that RNA structures in coronaviruses can adapt and evolve toward different viral variants, which has important implications for viral adaptation, pathogenicity, and future therapeutic strategies.

Predicting which proteins interact together from amino acid sequences is an important task. We develop a method to pair interacting protein sequences which leverages the power of protein language models trained on multiple sequence alignments (MSAs), such as MSA Transformer and the EvoFormer module of AlphaFold. We formulate the problem of pairing interacting partners among the paralogs of two protein families in a differentiable way. We introduce a method called Differentiable Pairing using Alignment-based Language Models (DiffPALM) that solves it by exploiting the ability of MSA Transformer to fill in masked amino acids in multiple sequence alignments using the surrounding context. MSA Transformer encodes coevolution between functionally or structurally coupled amino acids within protein chains. It also captures inter-chain coevolution, despite being trained on single-chain data. Relying on MSA Transformer without fine-tuning, DiffPALM outperforms existing coevolution-based pairing methods on difficult benchmarks of shallow multiple sequence alignments extracted from ubiquitous prokaryotic protein datasets. It also outperforms an alternative method based on a state-of-the-art protein language model trained on single sequences. Paired alignments of interacting protein sequences are a crucial ingredient of supervised deep learning methods to predict the three-dimensional structure of protein complexes. Starting from sequences paired by DiffPALM substantially improves the structure prediction of some eukaryotic protein complexes by AlphaFold-Multimer. It also achieves competitive performance with using orthology-based pairing.