Xi Zhu

Coxsackievirus A16 (CVA16) is one of the major pathogens responsible for hand, foot, and mouth disease (HFMD), for which no specific antiviral therapy is currently available. Neochlorogenic acid (NCGA) and chlorogenic acid (CGA) are a pair of chiral isomers with highly similar chemical structures. While the antiviral activity of CGA has been extensively investigated, that of NCGA remains largely unexplored. In our study, we found that NCGA exhibited antiviral activity against CVA16, whereas CGA was completely inactive. Notably, NCGA also displayed extremely low cytotoxicity, and its antiviral efficacy was further confirmed in vivo. We further identified RNA-binding motif protein 24 (RBM24) as a host factor involved in the antiviral effect of NCGA against CVA16, as its knockdown attenuated the antiviral activity of NCGA. Collectively, our findings not only identify a novel natural product against CVA16 but also provide clues for the discovery of host factors involved in CVA16 infection.

Enterovirus alphacoxsackie (EV-A) is a highly diverse viral species containing at least 25 serotypes with diverse biological and clinical characteristics. EV-A can cause diseases ranging from asymptomatic infections to severe neurological disorders, as well as mucocutaneous diseases such as hand, foot, and mouth disease. 2A, a cysteine protease expressed by EV-A, plays critical roles in virus–host interactions. Although 2A orthologs of different EV-A serotypes share consistent protease-catalytic motifs and cleavage patterns, they show functional diversity in interacting with cellular proteins, probably due to distinct protease-independent activities determined by the single amino acid polymorphisms (SAPs) among different 2A orthologs. However, routine sequence alignment and phylogenetic analysis can hardly identify the key SAP sites (kSAPs) contributing to the functional variance, mainly due to the high conservation of the proteins and the unequal weight of SAPs in determining protein function. Herein, we developed Single Amino Acid Polymorphism Statistics (SAAPS), an information-entropy (IE)-based algorithmic pipeline, to identify the functional kSAPs of EV-A 2A. The core principle of the algorithm is that the IE of the kSAPs can be neither too low (highly conserved sites not leading to variance) nor too high (random neutral mutations). Using SAAPS, we identified 56 kSAPs from 2A of 25 EV-A serotypes. Based on the kSAPs, the 2As can be clustered into three major groups with a few outliers, which was distinct from the clustering generated by phylogenetic analysis using the whole amino acid sequences. Functional verification with transcriptomic profiles of HEK-293T cells expressing different 2A variants revealed closer alignment of kSAP clustering than phylogenetic clustering. Notably, EV-A89, an outlier identified by kSAP clustering but not phylogenetic clustering, showed a unique expression pattern with an altered shift in the molecular weight, which suggested that it was related to three SAPs identified by SAAPS. This study presents SAAPS as a useful tool for prioritizing functionally relevant SAPs to guide mechanistic discovery and can be applied to highly conserved proteins like EV-A 2A.

Enterovirus alphacoxsackie (EV-A) is a highly diverse viral species containing at least 25 serotypes of viruses which show distinct infectivity and pathogenicity. Increasing studies show that EV-A protease 2A plays critical roles in virus-host interactions. Although 2A is usually considered as a non-structural protein highly conserved among different EV-A serotypes, its orthologs of different EV-A serotypes harbor abundant single amino acid polymorphisms (SAPs), probably contributing to the variance of infectivity and patho-genicity of EV-As. However, the SAP profile of EV-A 2A and its functional impacts have been poorly understood, mainly due to the unequal contribution to protein function of dif-ferent SAP sites. Herein, we developed Single Amino Acid Polymorphism Statistics (SAAPS), an information-entropy-based algorithmic pipeline, to identify key SAP sites (kSAPs) related to functional variance of EV-A 2A. As the result, we identified 56 kSAPs from 2A of 25 EV-A serotypes. Based on the kSAPs, the 2As can be clustered into three major groups with a few outliers, which was distinct from the clustering generated by phylogenetic analysis using the whole amino acid sequences. Functional verification with transcriptomic profiles of HEK-293T cells expressing different 2A variants revealed better phenotypic matching of kSAP-based clustering than that of phylogenetic clustering. No-tably, EV-A89, an outlier identified by kSAP clustering but not phylogenetic clustering, showed unique expressing and self-cleavage patterns which were not observed in other 2As. These findings demonstrated the good performance of SAAPS and functional SAP profile of EVA 2As, contributing to the understanding of the variance of EV-A infectivity and pathogenicity.