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Abstract Cartilaginous fishes (chondrichthyans: chimeras and elasmobranchs -sharks, skates, and rays) hold a key phylogenetic position to explore the origin and diversifications of jawed vertebrates. Here, we report and integrate reference genomic, transcriptomic, and morphological data in the small-spotted catshark Scyliorhinus canicula to shed light on the evolution of sensory organs. We first characterize general aspects of the catshark genome, confirming the high conservation of genome organization across cartilaginous fishes, and investigate population genomic signatures. Taking advantage of a dense sampling of transcriptomic data, we also identify gene signatures for all major organs, including chondrichthyan specializations, and evaluate expression diversifications between paralogs within major gene families involved in sensory functions. Finally, we combine these data with 3D synchrotron imaging and in situ gene expression analyses to explore chondrichthyan-specific traits and more general evolutionary trends of sensory systems. This approach brings to light, among others, novel markers of the ampullae of Lorenzini electrosensory cells, a duplication hotspot for crystallin genes conserved in jawed vertebrates, and a new metazoan clade of the transient-receptor potential (TRP) family. These resources and results, obtained in an experimentally tractable chondrichthyan model, open new avenues to integrate multiomics analyses for the study of elasmobranchs and jawed vertebrates. 

Plant secondary metabolites that defend leaves from herbivores also occur in floral nectar. While specialist herbivores often have adaptations providing resistance to these compounds in leaves, many social insect pollinators are generalists, and therefore are not expected to be as resistant to such compounds. The milkweeds, Asclepias spp., contain toxic cardenolides in all tissues including floral nectar. We compared the concentrations and identities of cardenolides between tissues of the North American common milkweed Asclepias syriaca, and then studied the effect of the predominant cardenolide in nectar, glycosylated aspecioside, on an abundant pollinator. We show that a generalist bumblebee, Bombus impatiens, a common pollinator in eastern North America, consumes less nectar with experimental addition of ouabain (a standard cardenolide derived from Apocynacid plants native to east Africa) but not with addition of glycosylated aspecioside from milkweeds. At a concentration matching that of the maximum in the natural range, both cardenolides reduced activity levels of bees after four days of consumption, demonstrating toxicity despite variation in behavioral deterrence (i.e., consumption). In vitro enzymatic assays of Na+/K+-ATPase, the target site of cardenolides, showed lower toxicity of the milkweed cardenolide than ouabain for B. impatiens, indicating that the lower deterrence may be due to greater tolerance to glycosylated aspecioside. In contrast, there was no difference between the two cardenolides in toxicity to the Na+/K+-ATPase from a control insect, the fruit fly Drosophila melanogaster. Accordingly, this work reveals that even generalist pollinators such as B. impatiens may have adaptations to reduce the toxicity of specific plant secondary metabolites that occur in nectar, despite visiting flowers from a wide variety of plants over the colony’s lifespan. 

Conjugated microporous polymers (CMPs) are an emerging class of porous organic polymers that combine -conjugated skeletons with permanent micropores. Since their first report in 2007, the enormous exploration of linkage types, building units, and synthetic methods for CMPs have facilitated their potential applications in various areas, from gas separations to energy storage. Owning to their unique construction, CMPs offer the opportunity for the precise design of conjugated skeletons and pore environment engineering, which allow the construction of functional porous materials at the molecular level. The capability to chemically alter CMPs to targeted applications allows for the fine adaptation of functionalities for the ever changing environments and necessities. Bifunctional CMPs are a branch of functionalized CMPs that have caught interest of researchers because of their inherent synergistic systems that can expand their applications and optimize their performance. This review attempts to discuss the rational design and synthesis for bifunctional CMPs and summarize their advanced applications. To conclude, our own perspective on the research prospect of this type of material is outlined. 

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83–98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.