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de Andrade KQ, Cirne-Santos CC. Antiviral Activity of Zinc Finger Antiviral Protein (ZAP) in Different Virus Families. Pathogens 2023; 12:1461. [PMID: 38133344 PMCID: PMC10747524 DOI: 10.3390/pathogens12121461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/14/2023] [Accepted: 12/15/2023] [Indexed: 12/23/2023] Open
Abstract
The CCCH-type zinc finger antiviral protein (ZAP) in humans, specifically isoforms ZAP-L and ZAP-S, is a crucial component of the cell's intrinsic immune response. ZAP acts as a post-transcriptional RNA restriction factor, exhibiting its activity during infections caused by retroviruses and alphaviruses. Its function involves binding to CpG (cytosine-phosphate-guanine) dinucleotide sequences present in viral RNA, thereby directing it towards degradation. Since vertebrate cells have a suppressed frequency of CpG dinucleotides, ZAP is capable of distinguishing foreign genetic elements. The expression of ZAP leads to the reduction of viral replication and impedes the assembly of new virus particles. However, the specific mechanisms underlying these effects have yet to be fully understood. Several questions regarding ZAP's mechanism of action remain unanswered, including the impact of CpG dinucleotide quantity on ZAP's activity, whether this sequence is solely required for the binding between ZAP and viral RNA, and whether the recruitment of cofactors is dependent on cell type, among others. This review aims to integrate the findings from studies that elucidate ZAP's antiviral role in various viral infections, discuss gaps that need to be filled through further studies, and shed light on new potential targets for therapeutic intervention.
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Affiliation(s)
- Kívia Queiroz de Andrade
- Laboratory of Immunology of Infectious Disease, Immunology Department, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, SP, Brazil
| | - Claudio Cesar Cirne-Santos
- Laboratory of Molecular Virology and Marine Biotechnology, Department of Cellular and Molecular Biology, Institute of Biology, Federal Fluminense University, Niterói 24020-150, RJ, Brazil
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Labani M, Beheshti A, Lovell NH, Alinejad-Rokny H, Afrasiabi A. KARAJ: An Efficient Adaptive Multi-Processor Tool to Streamline Genomic and Transcriptomic Sequence Data Acquisition. Int J Mol Sci 2022; 23:ijms232214418. [PMID: 36430895 PMCID: PMC9694301 DOI: 10.3390/ijms232214418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 11/22/2022] Open
Abstract
Here we developed KARAJ, a fast and flexible Linux command-line tool to automate the end-to-end process of querying and downloading a wide range of genomic and transcriptomic sequence data types. The input to KARAJ is a list of PMCIDs or publication URLs or various types of accession numbers to automate four tasks as follows; firstly, it provides a summary list of accessible datasets generated by or used in these scientific articles, enabling users to select appropriate datasets; secondly, KARAJ calculates the size of files that users want to download and confirms the availability of adequate space on the local disk; thirdly, it generates a metadata table containing sample information and the experimental design of the corresponding study; and lastly, it enables users to download supplementary data tables attached to publications. Further, KARAJ provides a parallel downloading framework powered by Aspera connect which reduces the downloading time significantly.
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Affiliation(s)
- Mahdieh Labani
- Biomedical Machine Learning Lab, The Graduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia
- Data Analytics Lab, Department of Computing, Macquarie University, Sydney, NSW 2109, Australia
| | - Amin Beheshti
- Data Analytics Lab, Department of Computing, Macquarie University, Sydney, NSW 2109, Australia
| | - Nigel H Lovell
- The Graduate School of Biomedical Engineering (GSBmE), University of New South Wales (UNSW), Sydney, NSW 2052, Australia
- Tyree Institute of Health Engineering (IHealthE), University of New South Wales (UNSW), Sydney, NSW 2052, Australia
| | - Hamid Alinejad-Rokny
- Biomedical Machine Learning Lab, The Graduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia
- UNSW Data Science Hub, University of New South Wales (UNSW), Sydney, NSW 2052, Australia
- Health Data Analytics Program, Centre for Applied Artificial Intelligence, Macquarie University, Sydney, NSW 2109, Australia
| | - Ali Afrasiabi
- Biomedical Machine Learning Lab, The Graduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia
- Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, University of Sydney, Sydney, NSW 2006, Australia
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Jiang L, Zhang Q, Xiao S, Si F. Deep decoding of codon usage strategies and host adaption preferences of soybean mosaic virus. Int J Biol Macromol 2022; 222:803-817. [PMID: 36167098 DOI: 10.1016/j.ijbiomac.2022.09.179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/13/2022] [Accepted: 09/17/2022] [Indexed: 11/05/2022]
Abstract
Soybean mosaic virus (SMV) has threatened the global yield of Leguminosae crops, but the mechanism of its infection, spread, and evolution remains unknown. A systemic analysis of 107 SMV strains was performed to explore the genome-wide codon usage profile and the various factors influencing the codon usage patterns of SMV, which provides insight into its molecular evolution and elucidates its unknown host adaptation pattern. The overall nucleotide composition and correlation analysis revealed that the preferred synonymous codons mostly end with A/U. Clustering by RSCU value of each strain and phylogenetic tree analysis showed that the SMV isolates studied were divided into four clades, with a low overall extent of codon usage bias (CUB) in SMV. According to the ENC, PR2, neutrality plot, and correspondence analysis, natural selection of geographical diversity may play a critical role in the CUB. Higher adaptability was shown in Glycine with SMV and more pressure was received by clade III. These findings could not only provide valuable information about the overall codon usage pattern of the SMV genome, but could also aid in the clarification of the involved mechanisms that dominate the codon usage patterns and genetic evolution of the SMV genome.
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Affiliation(s)
- Li Jiang
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510006, China
| | - Qiang Zhang
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou 450009, China
| | - Shimin Xiao
- Shanwei Marine Industry Institute, Shanwei Institute of Technology, Shanwei 516600, China.
| | - Fusheng Si
- Institute of Animal Science and Veterinary Medicine, Shanghai Academy of Agricultural Sciences, Shanghai Key Laboratory of Agricultural Genetics and Breeding, Shanghai Engineering Research Center of Breeding Pig, Shanghai 201106, China.
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