Cryo-electron microscopic structure of the nucleoprotein-RNA complex of the European filovirus, Lloviu virus

ヨーロッパに分布するエボラウイルス近縁ウイルスの増殖機構を解明 --広範囲の抗フィロウイルス療法の開発に期待--. 京都大学プレスリリース. 2023-04-10.Lloviu virus (LLOV) is a novel filovirus detected in Schreiber’s bats in Europe. The isolation of the infectious LLOV from bats has raised public health concerns. However, the virological and molecular characteristics of LLOV remain largely unknown. The nucleoprotein (NP) of LLOV encapsidates the viral genomic RNA to form a helical NP-RNA complex, which acts as a scaffold for nucleocapsid formation and de novo viral RNA synthesis. In this study, using single-particle cryo-electron microscopy, we determined two structures of the LLOV NP-RNA helical complex, comprising a full-length and a C-terminally truncated NP. The two helical structures were identical, demonstrating that the N-terminal region determines the helical arrangement of the NP. The LLOV NP-RNA protomers displayed a structure similar to that in the Ebola and Marburg virus, but the spatial arrangements in the helix differed. Structure-based mutational analysis identified amino acids involved in the helical assembly and viral RNA synthesis. These structures advance our understanding of the filovirus nucleocapsid formation, and provide a structural basis for the development of anti-filoviral therapeutics

Fast camera fingerprint search algorithm for source camera identification

To determine the source camera of a query image, the fingerprint from the query image needs to be compared with the fingerprints in the reference fingerprint database. Traditionally, the query fingerprint is compared with these reference fingerprints one by one in sequence. For a large database, however, such a brute-force search is inefficient and time-consuming. How to accurately locate the correct fingerprint in the reference fingerprint database is thus becoming a crucial problem for commercial applications of source camera identification. So far there have been few studies in literature addressing this problem. In this work, we propose a new solution to fast fingerprint search. We first store the information of the reference fingerprint digests in the separate-chaining hash table, and then introduce a new rule to select the candidate reference fingerprint digests before performing the correlation. The selection rule is incarnated with the search priority vector. Experimental results have shown that the proposed algorithm outperforms current algorithms