The design of CRISPR gRNAs requires accurate on-target efficiency predictions, which demand high-quality gRNA activity data and efficient modeling. To advance, we here report on the generation of on-target gRNA activity data for 10,592 SpCas9 gRNAs. Integrating these with complementary published data, we train a deep learning model, CRISPRon, on 23,902 gRNAs. Compared to existing tools, CRISPRon exhibits significantly higher prediction performances on four test datasets not overlapping with training data used for the development of these tools. Furthermore, we present an interactive gRNA design webserver based on the CRISPRon standalone software, both available via https://rth.dk/resources/crispr/. CRISPRon advances CRISPR applications by providing more accurate gRNA efficiency predictions than the existing tools.

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Foot-and-mouth disease virus (FMDV) causes a highly contagious, debilitating disease in cloven-Further mechanistic studies demonstrated that 3C pro induced proteasome-and caspase-independent protein degradation of karyopherin ␣1 (KPNA1), the nuclear localization signal receptor for tyrosine-phosphorylated STAT1, but not karyopherin ␣2, ␣3, or ␣4. Finally, we showed that the protease activity of 3C pro contributed to the degradation of KPNA1 and thus blocked STAT1/STAT2 nuclear translocation. Taken together, results of our experiments describe for the first time a novel mechanism by which FMDV evolves to inhibit IFN signaling and counteract host innate antiviral responses. IMPORTANCE We show that 3Cpro of FMDV antagonizes the JAK-STAT signaling pathway by blocking STAT1/STAT2 nuclear translocation. Furthermore, 3C pro induces KPNA1 degradation, which is independent of proteasome and caspase pathways. The protease activity of 3C pro contributes to the degradation of KPNA1 and governs the ability of 3C pro to inhibit the JAK-STAT signaling pathway. This study uncovers a novel mechanism evolved by FMDV to antagonize host innate immune responses.

Chinese shrimp ( Penaeus chinensis) is widely cultured and consumed in Asia but is also a major food allergen locally. Although they may be the foundation for preventing and treating allergies, the allergenic epitopes of the major allergens tropomyosin (TM) and arginine kinase (AK) in Penaeus chinensis have not been identified. Here, we applied Immunoinfo-CB (immunoinformatics coupled with competitive-binding strategy) to address the point. Potential allergenic epitopes of TM and AK were predicted by multiple immunoinformatics tools, followed by validating with inhibitory dot-blot assay, indirect competition ELISA, and mast cell degranulation assay. Furthermore, critical amino acids in allergenic epitopes were also identified by Immunoinfo-CB. Our findings provide new insight into allergenic epitopes and critical amino acids of TM and AK responsible for the anaphylactic response. The Immunoinfo-CB therefore offers promises for characterization of IgE-binding epitopes that might be used as new targets for immunotherapy of food allergy.

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