Identification and Evolutionary Analysis of the Widely Distributed CAP Superfamily in Spider Venom.

Venom plays a crucial role in the defense and predation of venomous animals. Spiders (Araneae) are among the most successful predators and have a fascinating venom composition. Their venom mainly contains disulfide-rich peptides and large proteins. Here, we analyzed spider venom protein families, utilizing transcriptomic and genomic data, and highlighted their similarities and differences. We show that spiders have specific combinations of toxins for better predation and defense, typically comprising a core toxin expressed alongside several auxiliary toxins. Among them, the CAP superfamily is widely distributed and highly expressed in web-building Araneoidea spiders. Our analysis of evolutionary relationships revealed four subfamilies (subA-subD) of the CAP superfamily that differ in structure and potential functions. CAP proteins are composed of a conserved CAP domain and diverse C-terminal domains. CAP subC shares similar domains with the snake ion channel regulator svCRISP proteins, while CAP subD possesses a sequence similar to that of insect venom allergen 5 (Ag5). Furthermore, we show that gene duplication and selective expression lead to increased expression of CAP subD, making it a core member of the CAP superfamily. This study sheds light on the functional diversity of CAP subfamilies and their evolutionary history, which has important implications for fully understanding the composition of spider venom proteins and the core toxin components of web-building spiders.

A molecular atlas reveals the tri-sectional spinning mechanism of spider dragline silk.

The process of natural silk production in the spider major ampullate (Ma) gland endows dragline silk with extraordinary mechanical properties and the potential for biomimetic applications. However, the precise genetic roles of the Ma gland during this process remain unknown. Here, we performed a systematic molecular atlas of dragline silk production through a high-quality genome assembly for the golden orb-weaving spider Trichonephila clavata and a multiomics approach to defining the Ma gland tri-sectional architecture: Tail, Sac, and Duct. We uncovered a hierarchical biosynthesis of spidroins, organic acids, lipids, and chitin in the sectionalized Ma gland dedicated to fine silk constitution. The ordered secretion of spidroins was achieved by the synergetic regulation of epigenetic and ceRNA signatures for genomic group-distributed spidroin genes. Single-cellular and spatial RNA profiling identified ten cell types with partitioned functional division determining the tri-sectional organization of the Ma gland. Convergence analysis and genetic manipulation further validated that this tri-sectional architecture of the silk gland was analogous across Arthropoda and inextricably linked with silk formation. Collectively, our study provides multidimensional data that significantly expand the knowledge of spider dragline silk generation and ultimately benefit innovation in spider-inspired fibers.

Venn diagrams in bioinformatics.

Venn diagrams are widely used tools for graphical depiction of the unions, intersections and distinctions among multiple datasets, and a large number of programs have been developed to generate Venn diagrams for applications in various research areas. However, a comprehensive review comparing these tools has not been previously performed. In this review, we collect Venn diagram generators (i.e. tools for visualizing the relationships of input lists within a Venn diagram) and Venn diagram application tools (i.e. tools for analyzing the relationships between biological data and visualizing them in a Venn diagram) to compare their functional capacity as follows: ability to generate high-quality diagrams; maximum datasets handled by each program; input data formats; output diagram styles and image output formats. We also evaluate the picture beautification parameters of the Venn diagram generators in terms of the graphical layout and briefly describe the functional characteristics of the most popular Venn diagram application tools. Finally, we discuss the challenges in improving Venn diagram application tools and provide a perspective on Venn diagram applications in bioinformatics. Our aim is to assist users in selecting suitable tools for analyzing and visualizing user-defined datasets.

Interface Design of SnO2@PANI Nanotube With Enhanced Sensing Performance for Ammonia Detection at Room Temperature.

Gas sensors with excellent stability and a high response at room temperature has drawn a great deal of attention and demand for them is huge. Surface designs provide inspiration toward making more useful sensor devices. The facile electrospinning process and Ar plasma treatment are used to fabricate rich and stable oxygen vacancies that contain a core-shell structured SnO2 polyaniline (PANI) nanotube. It shows that the induced surface oxygen vacancies would accelerate the PANI shell to generate more protons, which can enhance its sensor responsibility through reacting with the target Ammonia (NH3) gas. It was also found that the obtained oxygen vacancies can be well-protected by the coated PANI shell, which enhance and stabilize the gas response. It shows that the room temperature for the gas response of NH3 can reach up to 35.3 at 100 ppm. Finally, its good stability is demonstrated by the response-recovery performances carried out over 3 months and multiple cycles. This work indicates that this well-designed PANI-coated plasma-treated SnO2 is a potential way to design ammonia gas sensors.